Systems and methods for generating a nutrition program

Abstract

Developing a nutrition program personalized to a user may comprise: causing display of a first query to the user, wherein a first user response is used to determine a biographical representation of the user; causing display of a second query to the user, wherein a second user response to the second query is used to determine one or both of one or more objectives of the user or a symptom representation of the user; obtaining, based at least in part on the biographical representation and one or both of the one or more objectives or the symptom representation, a nutrition program corresponding to one or more nutrients; and causing display of the nutrition program corresponding to the one or more nutrients, wherein the one or more nutrients aid in one or both of achieving the one or more objectives or addressing one or more symptoms corresponding to the symptom representation.

Description

SYSTEMS AND METHODS FOR GENERATING A NUTRITION PROGRAMCROSS REFERENCE

[0001] This application claims the benefit of U.S. Provisional Application No. 63 / 527,798, filed on July 19, 2023, which is incorporated herein by reference in its entirety.BACKGROUND

[0002] People have different nutrient requirements and respond differently to food given the differences in their biology, lifestyle, environment, and health history. One person may digest and absorb a particular nutrient quickly, while others may not transport or utilize another as effectively based on their genetics, for example. Some medications deplete important nutrients, and some dietary restrictions can impact an individual’s intake of important nutrients. Some lifestyle factors can accelerate aging in some, while having little effect in others. All this individual variability makes it very challenging to take a one-size-fits-all approach to nutrition. There is therefore a strong need for personalized approaches to nutrition and food.SUMMARY

[0003] Systems, methods, computer-readable media, and techniques described herein can be used to provide a personalized nutrition program to an individual, including what nutrients and supplements will be most beneficial based on the individual’s health priorities, symptoms, and biographical representation.

[0004] In one aspect, a method for developing a nutrition program personalized to a user comprises: (a) causing display of, using a computer system and a graphical display, a first query to the user, wherein a first user response from the user to the first query is used to determine a biographical representation of the user; (b) causing display of, using the computer system and the graphical display, a second query to the user, wherein a second user response to the second query is used to determine one or both of (i) one or more objectives of the user or (ii) a symptom representation of the user; (c) obtaining, using the computer system, based at least in part on the biographical representation and one or both of (i) the one or more objectives or (ii) the symptom representation, a nutrition program corresponding to one or more nutrients; and (d) causing display of, using the computer system and the graphical display, the nutrition program corresponding to the one or more nutrients, whereinthe one or more nutrients aid in one or both of (i) achieving the one or more objectives or (ii) addressing one or more symptoms corresponding to the symptom representation. In some embodiments, the first query asks the user to respond to a list of biographical questions. In some embodiments, the list of biographical questions comprises one or more questions related to demographic information of the user or a family of the user. In some embodiments, the demographic information comprises an age of the user. In some embodiments, the demographic information comprises a sex of the user. In some embodiments, the demographic information comprises a gender of the user. In some embodiments, the demographic information comprises a geographical location of the user. In some embodiments, the demographic information comprises an ancestry of the user. In some embodiments, the list of biographical questions comprises one or more questions related to a medical history of the user or a family of the user. In some embodiments, the medical history comprises one or more medications taken by the user. In some embodiments, the medical history comprises a chronic disease state of the user. In some embodiments, the list of biographical questions comprises one or more questions related to lifestyle information of the user or family of the user. In some embodiments, the lifestyle information comprises an eating habit of the user. In some embodiments, the lifestyle information comprises an exercise habit of the user. In some embodiments, the lifestyle information comprises an alcohol consumption habit of the user. In some embodiments, the lifestyle information comprises an activity level of the user. In some embodiments, the lifestyle information comprises a special diet or dietary restriction of the user. In some embodiments, the list of biographical questions comprises one or more questions related to one or more physical attributes of the user. In some embodiments, the one or more physical attributes of the user comprises a skin color of the user. In some embodiments, the one or more physical attributes of the user comprises a weight of the user. In some embodiments, the one or more physical attributes of the user comprises a height of the user. In some embodiments, the one or more physical attributes of the user comprises a waist circumference of the user. In some embodiments, the one or more physical attributes of the user comprises a skin color of the user. In some embodiments, the one or more physical attributes of the user comprises a body mass index of the user. In some embodiments, the second query asks the user to identify the one or more objectives that correspond to one or more health goals from a list of health goals. In some embodiments, the list of health goals comprises an immune health goal. In some embodiments, the list of health goals comprises a gastrointestinal or gut health goal. In some embodiments, the list of health goals comprises an aging health goal. In some embodiments,the aging health goal comprises prevention of cancer, sarcopenia, or osteoporosis, or a combination thereof. In some embodiments, the list of health goals comprises a neurological or brain health goal. In some embodiments, the neurological or brain health goal comprises preventing cognitive decline or dementia. In some embodiments, the list of health goals comprises a metabolic health goal. In some embodiments, the metabolic health goal comprises weight or diabetes control. In some embodiments, the list of health goals comprises a cardiovascular or heart health goal. In some embodiments, the list of health goals comprises a performance-related goal. In some embodiments, the one or more health goals comprises a plurality of health goals, and the second query requires the user to rank the plurality of health goals. In some embodiments, the second query asks the user to identify the symptom representation from a list of symptoms, wherein the symptom representation corresponds to all symptoms that the user suffers from. In some embodiments, the list of symptoms comprises one or more physical energy or health-related symptoms. In some embodiments, the one or more physical energy or health-related symptoms comprises fatigue. In some embodiments, the one or more physical energy or health-related symptoms comprises constipation. In some embodiments, the one or more physical energy or health- related symptoms comprises skin aging. In some embodiments, the one or more physical energy or health-related symptoms comprises poor exercise recovery. In some embodiments, the one or more physical energy or health-related symptoms comprises insomnia or sleep issues. In some embodiments, the one or more physical energy or health-related symptoms comprises joint pain. In some embodiments, the one or more physical energy or health- related symptoms comprises premenstrual syndrome (PMS). In some embodiments, the list of symptoms comprises one or more mental-health related symptoms. In some embodiments, the one or more mental-health related symptoms comprises anxiety. In some embodiments, the one or more mental-health related symptoms comprises depression. In some embodiments, the one or more mental-health related symptoms comprises poor appetite control. In some embodiments, the one or more mental-health related symptoms comprises difficulty managing stress. In some embodiments, the list of symptoms comprises one or more mental-acuity related symptoms. In some embodiments, the one or more mental-acuity related symptoms comprises brain fog. In some embodiments, the list of symptoms comprises one or more immune-related symptoms. In some embodiments, the one or more immune- related symptoms comprises frequent sickness. In some embodiments, the nutrition program recommends one or more foods, and wherein the foods provide the determined key one or more nutrients to the user. In some embodiments, determining the nutrition programcomprises selecting, with the aid of the computer system and based on the one or more key nutrients, the recommended one or more foods from a list of foods. In some embodiments, the nutrition program recommends one or more supplements. In some embodiments, a first supplement of the one or more supplements aids in achieving the one or more health goals of the user. In some embodiments, a second supplement of the one or more supplements aids in alleviating one or more of the symptoms that the user suffers from. In some embodiments, determining the nutrition program comprises selecting, using the computer system and based on the one or more key nutrients, the recommended one or more supplements from a list of supplements. In some embodiments, the one or more nutrients comprise a plurality of nutrients. In some embodiments, the one or more key nutrients are selected from a list of nutrients. In some embodiments, the list of nutrients comprises Vitamin B 12, Vitamin D, Omega-3, Magnesium, Choline, Polyphenols, Soluble Fiber, or Vitamin C. In some embodiments, the list of nutrients comprises Vitamin B12, Vitamin D, Omega-3, Magnesium, Choline, Polyphenols, Soluble Fiber, and Vitamin C. In some embodiments, the obtaining the nutrition program corresponding to the one or more key nutrients at (c) is further based on the genetic report of the user. In some embodiments, the genetic report of the user comprises epigenetic data of the user. In some embodiments, the genetic report comprises one or more genetic predispositions of the user. In some embodiments, the biomarker data is obtained from analyzing a body fluid sample from the user. In some embodiments, the body fluid comprises blood. In some embodiments, the body fluid comprises plasma. In some embodiments, the body fluid comprises urine. In some embodiments, the body fluid comprises saliva. In some embodiments, the obtaining the nutrition program corresponding to the one or more key nutrients at (c) is further based on the data for levels of the one or more biomarkers of the user. In some embodiments, the one or more biomarkers comprise Vitamin D. In some embodiments, the one or more biomarkers comprise magnesium. In some embodiments, the one or more biomarkers comprise omega-3. In some embodiments, the one or more biomarkers comprise choline. In some embodiments, the one or more biomarkers comprise Vitamin B 12. In some embodiments, the one or more biomarkers comprise polyphenols. In some embodiments, the one or more biomarkers comprise soluble fiber. In some embodiments, the one or more biomarkers comprise Vitamin C. In some embodiments, the obtaining the nutrition program corresponding to the one or more key nutrients at (c) is further based on biomarker data for levels of the one or more biomarkers of the user, epigenetic data of the user, and one or more genetic dispositions of the user. In some embodiments, the computer system prompts the user to cause the repetition of operations (a)-(e) at a given time interval. In some embodiments, the causing display of the second query to the user at (b) comprises determining both the one or more objectives of the user and the symptom representation of the user, and wherein obtaining the nutrition program corresponding to the one or more nutrients at (c) comprises (i) determining a first relative weight of the biographical representation of the user, (ii) determining a second relative weight of the one or more objectives of the user, and (iii) determining a third relative weight of the symptom representation of the user, and wherein determining the nutrition program is based on a combination of the first relative weight, the second relative weight, and the third relative weight. In some embodiments, the first relative weight of the biographical representation comprises a plurality of weights for each nutrient in a list of nutrients. In some embodiments, the biographical representation of the user comprises a plurality of biographical parameters, each biographical parameter comprising a relative weight for each nutrient of the list of nutrients. In some embodiments, the second relative weight of the one or more objectives comprises a plurality of weights for each nutrient in a list of nutrients. In some embodiments, the one or more objectives comprises a plurality of health goals, each health goal comprising a relative weight for each nutrient of the list of nutrients. In some embodiments, the third relative weight of the symptom representation comprises a plurality of weights for each nutrient in a list of nutrients. In some embodiments, the symptom representation comprises a plurality of symptoms, each symptom comprising a relative weight for each nutrient of the list of nutrients. In some embodiments, the nutrition program comprises a recommendation of one or more food options from the plurality of food options to the user. In some embodiments, a restaurant menu comprises the plurality of food options. In some embodiments, the recommendation of the one or more food options comprise a recommendation to order the one or more food options at a restaurant corresponding to the restaurant menu. In some embodiments, a store comprises the plurality of food options. In some embodiments, the recommendation of the one or more food options comprise a recommendation to purchase the one or more food options at the store. In some embodiments, one or more of a refrigerator, a freezer, or a pantry comprises the plurality of food options. In some embodiments, the recommendation of the one or more food options comprise a recommendation to cook the one or more food options at a kitchen corresponding to the one or more of the refrigerator, the freezer, or the pantry.

[0005] In another aspect, a system for developing a nutrition program personalized to a user, comprises: a computer system operatively coupled to a graphical display, wherein thecomputer system comprises machine-executable code that, upon execution by one or more computer processors, implements the method of any one of the above aspects / embodiments.

[0006] In another aspect, a system for developing a nutrition program personalized to a user comprises: a computer system operatively coupled to a graphical display, wherein the computer system comprises machine-executable code that, upon execution by one or more computer processors, implements operations comprising: (a) presenting a first query to the user, wherein a first user response from the user to the first query is used to determine a biographical representation of the user; (b) presenting a second query to the user, wherein a second user response to the second query is used to determine one or both of (i) one or more objectives of the user, or (ii) a symptom representation of the user; (c) determining, based at least in part on the biographical representation and one or both of (i) the one or more objectives or (ii) the symptom representation, a nutrition program corresponding to one or more nutrients; and (e) displaying the nutrition program corresponding to the one or more nutrients, wherein the one or more nutrients aid in one or both of (i) achieving the one or more objectives of the user or (ii) addressing one or more symptoms corresponding to the symptom representation. In some embodiments, the first query asks the user to respond to a list of biographical questions. In some embodiments, the list of biographical questions comprises one or more questions related to demographic information of the user or a family of the user. In some embodiments, the demographic information comprises an age of the user. In some embodiments, the demographic information comprises a sex of the user. In some embodiments, the demographic information comprises a gender of the user. In some embodiments, the demographic information comprises a geographical location of the user. In some embodiments, the demographic information comprises an ancestry of the user. In some embodiments, the list of biographical questions comprises one or more questions related to a medical history of the user or a family of the user. In some embodiments, the medical history comprises one or more medications taken by the user. In some embodiments, the medical history comprises a chronic disease state of the user. In some embodiments, the list of biographical questions comprises one or more questions related to lifestyle information of the user or family of the user. In some embodiments, the lifestyle information comprises an eating habit of the user. In some embodiments, the lifestyle information comprises an exercise habit of the user. In some embodiments, the lifestyle information comprises an alcohol consumption habit of the user. In some embodiments, the lifestyle information comprises an activity level of the user. In some embodiments, the lifestyle information comprises a special diet or dietary restriction of the user. In some embodiments, the list ofbiographical questions comprises one or more questions related to one or more physical attributes of the user. In some embodiments, the one or more physical attributes of the user comprises a skin color of the user. In some embodiments, the one or more physical attributes of the user comprises a weight of the user. In some embodiments, the one or more physical attributes of the user comprises a height of the user. In some embodiments, the one or more physical attributes of the user comprises a waist circumference of the user. In some embodiments, the one or more physical attributes of the user comprises a skin color of the user. In some embodiments, the one or more physical attributes of the user comprises a body mass index of the user. In some embodiments, the second query asks the user to identify the one or more objectives that correspond to one or more health goals from a list of health goals. In some embodiments, the list of health goals comprises an immune health goal. In some embodiments, the list of health goals comprises a gastrointestinal or gut health goal. In some embodiments, the list of health goals comprises an aging health goal. In some embodiments, the aging health goal comprises prevention of cancer, sarcopenia, or osteoporosis, or a combination thereof. In some embodiments, the list of health goals comprises a neurological or brain health goal. In some embodiments, the neurological or brain health goal comprises preventing cognitive decline or dementia. In some embodiments, the list of health goals comprises a metabolic health goal. In some embodiments, the metabolic health goal comprises weight or diabetes control. In some embodiments, the list of health goals comprises a cardiovascular or heart health goal. In some embodiments, the list of health goals comprises a performance-related goal. In some embodiments, the one or more health goals comprises a plurality of health goals, and the second query requires the user to rank the plurality of health goals. In some embodiments, the second query asks the user to identify the symptom representation from a list of symptoms, wherein the symptom representation corresponds to all symptoms that the user suffers from. In some embodiments, the list of symptoms comprises one or more physical energy or health-related symptoms. In some embodiments, the one or more physical energy or health-related symptoms comprises fatigue. In some embodiments, the one or more physical energy or health-related symptoms comprises constipation. In some embodiments, the one or more physical energy or health- related symptoms comprises skin aging. In some embodiments, the one or more physical energy or health-related symptoms comprises poor exercise recovery. In some embodiments, the one or more physical energy or health-related symptoms comprises insomnia or sleep issues. In some embodiments, the one or more physical energy or health-related symptoms comprises joint pain. In some embodiments, the one or more physical energy or health-related symptoms comprises premenstrual syndrome (PMS). In some embodiments, the list of symptoms comprises one or more mental-health related symptoms. In some embodiments, the one or more mental-health related symptoms comprises anxiety. In some embodiments, the one or more mental-health related symptoms comprises depression. In some embodiments, the one or more mental-health related symptoms comprises poor appetite control. In some embodiments, the one or more mental-health related symptoms comprises difficulty managing stress. In some embodiments, the list of symptoms comprises one or more mental-acuity related symptoms. In some embodiments, the one or more mental-acuity related symptoms comprises brain fog. In some embodiments, the list of symptoms comprises one or more immune-related symptoms. In some embodiments, the one or more immune- related symptoms comprises frequent sickness. In some embodiments, the nutrition program recommends one or more foods, and wherein the foods provide the determined key one or more nutrients to the user. In some embodiments, determining the nutrition program comprises selecting, using the computer system and based on the one or more key nutrients, the recommended one or more foods from a list of foods. In some embodiments, the nutrition program recommends one or more supplements. In some embodiments, a first supplement of the one or more supplements aids in achieving the one or more health goals of the user. In some embodiments, a second supplement of the one or more supplements aids in alleviating one or more of the symptoms that the user suffers from. In some embodiments, determining the nutrition program comprises selecting, using the computer system and based on the one or more key nutrients, the recommended one or more supplements from a list of supplements. In some embodiments, the one or more nutrients comprise a plurality of nutrients. In some embodiments, the one or more key nutrients are selected from a list of nutrients. In some embodiments, the list of nutrients comprises Vitamin B12, Vitamin D, Omega-3, Magnesium, Choline, Polyphenols, Soluble Fiber, or Vitamin C. In some embodiments, the list of nutrients comprises Vitamin Bl 2, Vitamin D, Omega-3, Magnesium, Choline, Polyphenols, Soluble Fiber, and Vitamin C. In some embodiments, the obtaining the nutrition program corresponding to the one or more key nutrients at (c) is further based on the genetic report of the user. In some embodiments, the genetic report of the user comprises epigenetic data of the user. In some embodiments, the genetic report comprises one or more genetic predispositions of the user. In some embodiments, the biomarker data is obtained from analyzing a body fluid sample from the user. In some embodiments, the body fluid comprises blood. In some embodiments, the body fluid comprises plasma. In some embodiments, the body fluid comprises urine. In some embodiments, the body fluid comprises saliva. In someembodiments, the obtaining the nutrition program corresponding to the one or more key nutrients at (c) is further based on the data for levels of the one or more biomarkers of the user. In some embodiments, the one or more biomarkers comprise Vitamin D. In some embodiments, the one or more biomarkers comprise magnesium. In some embodiments, the one or more biomarkers comprise omega-3. In some embodiments, the one or more biomarkers comprise choline. In some embodiments, the one or more biomarkers comprise Vitamin B 12. In some embodiments, the one or more biomarkers comprise polyphenols. In some embodiments, the one or more biomarkers comprise soluble fiber. In some embodiments, the one or more biomarkers comprise Vitamin C. In some embodiments, the obtaining the nutrition program corresponding to the one or more key nutrients at (c) is further based on biomarker data for levels of the one or more biomarkers of the user, epigenetic data of the user, and one or more genetic dispositions of the user. In some embodiments, the computer system prompts the user to cause the repetition of operations (a)- (e) at a given time interval. In some embodiments, the causing display of the second query to the user at (b) comprises determining both the one or more objectives of the user and the symptom representation of the user, and wherein obtaining the nutrition program corresponding to the one or more nutrients at (c) comprises (i) determining a first relative weight of the biographical representation of the user, (ii) determining a second relative weight of the one or more objectives of the user, and (iii) determining a third relative weight of the symptom representation of the user, and wherein determining the nutrition program is based on a combination of the first relative weight, the second relative weight, and the third relative weight. In some embodiments, the first relative weight of the biographical representation comprises a plurality of weights for each nutrient in a list of nutrients. In some embodiments, the biographical representation of the user comprises a plurality of biographical parameters, each biographical parameter comprising a relative weight for each nutrient of the list of nutrients. In some embodiments, the second relative weight of the one or more objectives comprises a plurality of weights for each nutrient in a list of nutrients. In some embodiments, the one or more objectives comprises a plurality of health goals, each health goal comprising a relative weight for each nutrient of the list of nutrients. In some embodiments, the third relative weight of the symptom representation comprises a plurality of weights for each nutrient in a list of nutrients. In some embodiments, the symptom representation comprises a plurality of symptoms, each symptom comprising a relative weight for each nutrient of the list of nutrients. In some embodiments, the nutrition program comprises a recommendation of one or more food options from the plurality of food optionsto the user. In some embodiments, a restaurant menu comprises the plurality of food options. In some embodiments, the recommendation of the one or more food options comprise a recommendation to order the one or more food options at a restaurant corresponding to the restaurant menu. In some embodiments, a store comprises the plurality of food options. In some embodiments, the recommendation of the one or more food options comprise a recommendation to purchase the one or more food options at the store. In some embodiments, one or more of a refrigerator, a freezer, or a pantry comprises the plurality of food options. In some embodiments, the recommendation of the one or more food options comprise a recommendation to cook the one or more food options at a kitchen corresponding to the one or more of the refrigerator, the freezer, or the pantry.INCORPORATION BY REFERENCE

[0007] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. In some embodiments, the novel features of the present disclosure are set forth with particularity in the appended claims. In some embodiments, a better understanding of the features and advantages of the present disclosure will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the disclosure are utilized, and the accompanying drawings of which:

[0009] FIG. 1 shows a flow chart of a method for presenting at least three queries to a user to provide a personalized nutrition program to the user;

[0010] FIG. 2 shows a flow chart of a method for presenting at least three queries to a user and obtaining a genetic report of the user to provide a personalized nutrition program to the user;

[0011] FIG. 3 shows a flow chart of a method for presenting at least three queries to a user and obtaining omic data of the user to provide a personalized nutrition program to the user;

[0012] FIG. 4 shows a flow chart of a method for presenting at least three queries to a user and obtaining data for levels of one or more biomarkers of the user to provide a personalized nutrition program to the user;

[0013] FIG. 5 shows a flow chart of a method for presenting at least three queries to a user and obtaining: (1) a genetic report, (2) omic data, and (3) data for levels of one or more biomarkers of the user to provide a personalized nutrition program to the user;

[0014] FIG. 6 shows a flow chart of a method for presenting at least three queries to a user to provide a personalized nutrition program to the user where the user retakes the questionnaire after one or more objectives are achieved and / or one or more symptoms are relieved;

[0015] FIG. 7 shows a flow chart of a method for presenting at least three queries to a user to provide a personalized nutrition program to the user where the user retakes the questionnaire at a given time interval;

[0016] FIG. 8 shows a flow chart of a method for presenting at least three queries to a user to provide a personalized nutrition program and having a professional review the personalized nutrition program, where optionally, the professional can update the algorithm used to output the personalized nutrition program;

[0017] FIG. 9 shows a flow chart of a method for presenting at least three queries to a user to provide a personalized nutrition program and having a professional review the personalized nutrition program, where optionally, the professional can update the queries periodically;

[0018] FIG. 10 shows a computer system that is programmed or otherwise configured to implement methods provided herein;

[0019] FIG. 11A shows a user interface presenting a meal planner personalized for a nutrition program; and

[0020] FIG. 11B shows another user interface presenting a meal planner personalized for a nutrition program.DETAILED DESCRIPTION

[0021] While various embodiments have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions may occur to those skilled in the art without departing from the systems, the methods, the computer-readable media, and the techniques provided herein.

[0022] In some embodiments, the systems, the methods, the computer-readable media, and the techniques disclosed herein provide for presenting one or more queries to a user in theform of questionnaire questions and receiving the user’s responses. A processor can then be used to interpret the response based on a set of reference information. The user’s responses to the one or more queries, alone or in combination with additional data points, can be used to generate a personalized nutrition program for the user. The personalized nutrition program may list one or more key nutrients determined to aid in one or more of (i) achieving one or more objectives of the user or (ii) alleviating one or more of the symptoms that the user suffers from. The personalized nutrition program may be displayed to the user using an interactive graphical display.Questionnaire

[0023] In some cases, a first query can be presented to a user. The first query can be presented using a computer system and a graphical display. In some cases, the graphical display may include an interactive graphical display. The first query can be used to establish a biographical representation of the user. In some cases, the biographical representation of a user may include a biographical profile of the user. In some cases, the first query asks the user to respond to a list of biographical questions.

[0024] The biographical questions may be related to demographic information, including the age, sex, gender, geographical location, occupation, or ancestry of the user.

[0025] The biographical questions may be related to a user’s medical history, including one or more medications taken by the user, recent surgeries, or a chronic disease state of the user.

[0026] In some cases, the list of biographical questions is related to the lifestyle of the user, including eating habits, exercise habits, smoking habits, alcohol consumption, activity level, caffeine intake, drug use, or a special diet or dietary restriction.

[0027] In some cases, the list of biographical questions is related to one or more physical attributes of the user. Physical attributes may include skin color, weight, height, a waist circumference, a body mass index, a body fat percentage, a cholesterol level, or a triglyceride level of the user.

[0028] In some cases, a second query can be presented to a user. The second query can be presented using a computer system and a graphical display. In some cases, the graphical display may include an interactive graphical display. The second query can be used to identify one or more objectives of a user. In some cases, the one or more objectives of a user may include one or more health goals of the user.

[0029] The second query may present a list of one or more objectives for a user to choose from and / or rank in order of importance. Objectives may include immune health, gastrointestinal or gut health, aging health (cancer, sarcopenia, osteoporosis), neurological orbrain health (cognitive decline, dementia), metabolic health (weight, diabetes), cardiovascular or heart health, or a performance-related goal.

[0030] In some cases, a third query can be presented to a user. The third query can be presented using a computer system and a graphical display. The third query can be used to identify or rank symptoms a user is experiencing to, for example, establish a symptom representation.

[0031] The third query may present a list of symptoms for a user to choose from and / or rank in order of severity. Symptoms may include physical energy or health related symptoms such as fatigue, constipation, skin aging, poor exercise recovery, insomnia or sleep issues, joint pain, or premenstrual disorder (PMS), for example. Symptoms may include mental-health related symptoms such as anxiety, depression, poor appetite control, or difficulty managing stress, for example. Symptoms may include one or more mental acuity related symptoms such as brain fog, for example. Symptoms may include one or more immune-related symptoms such as frequent sickness, for example.Personalized Nutrition Program

[0032] The systems, the methods, the computer-readable media, and the techniques described herein may be used to output a personalized nutrition program based on a user’s responses to one or more queries. In some cases, the nutrition program may include a nutrition plan. The nutrition program may include one or more key nutrients that a subject should include in his or her diet. The one or more key nutrients may aid in achieving one or more objectives of the user, alleviating one or more of the symptoms that the user suffers from, or a combination thereof. The personalized nutrition program can be displayed to the user using a graphical display. In some cases, the graphical display may include an interactive graphical display.

[0033] In some cases, the nutrition program recommends one or more foods, and the foods provide the determined key one or more nutrients to the user. The one or more foods may be selected, using the computer system and based on the identified key nutrients, from a list of foods. In some cases, the list of foods may include foods on a menu, such as, a restaurant menu, a bar menu, etc. To obtain the menu, in one example, a photograph of the menu may be obtained (e.g., via a smartphone camera). In another example, a restaurant or bar name may be provided such that the menu may be obtained. In some cases, the list of foods may include foods in a store, such as, a convenience store, a grocery store, a market, etc. In this case, the list of foods may be obtained from a photograph (e.g., captured by a smartphone camera from inside the grocery store, the convenience store, the market, etc.) or from importing stock data (e.g., via integrations with the grocery store, the convenience store, themarket, etc.). In some cases, the list of foods may include foods in a home (e.g., in a refrigerator, in a freezer, in a pantry, etc.). In this case, the list of foods may be obtained from a photograph (e.g., captured by a smartphone camera from inside the home) or from importing data from smart appliances (e.g., a smart refrigerator). Across these cases, the photographs may be, in some examples, photographs of the food item itself (e.g., leveraging computer vision to identify the food item. In other examples, the photographs may be of a written description of the food item (e.g., on packaging, on a label, on a menu, etc.). In other examples, the photographs may be of a code corresponding to the food item (e.g., a QR code, a barcode, a UPC code, etc.).

[0034] In some cases, the nutrition program recommends one or more supplements to the user. In some cases, a first supplement aids in achieving one or more objectives of the user. In some cases, a second supplement aids in alleviating one or more of the symptoms that the user suffers from. The supplements may be selected, using the computer system and based on the identified key nutrients, from a list of supplements.

[0035] In some cases, the nutrition algorithm outputs one or more key nutrients. In some cases, the nutrition algorithm outputs three key nutrients. In some cases, the key nutrients are chosen from a list of nutrients. The list of nutrients may include Vitamin B12, Vitamin D, Omega-3, Magnesium, Choline, Polyphenols, Soluble Fiber, or Vitamin C. In some cases, the list of nutrients comprises Vitamin B 12, Vitamin D, Omega-3, Magnesium, Choline, Polyphenols, Soluble Fiber, and Vitamin C.

[0036] In some cases, the method further comprises obtaining a genetic report of the user, which can be used to confirm and / or supplement a user’s personalized nutrition program. The genetic report may include epigenetic data of the user. In some cases, the genetic report comprises one or more genetic predispositions of the user. In some cases, the method further comprises obtaining omic data of the user, which can be used to confirm and / or supplement a user’s personalized nutrition program. Omic data may include genomic data, epigenomic data, microbiomic data, proteomic data, glycomic data, and / or metabolomic data, or any combination thereof.

[0037] In some cases, the method further comprises obtaining epigenetic data of the user, which can be used to confirm and / or supplement a user’s personalized nutrition program. Epigenetic data can include epigenetic changes including DNA methylation, histone modification, and / or non-coding RNA.

[0038] In some cases, the method further comprises obtaining data for levels of one or more biomarkers of the user, which can be used to confirm and / or supplement a user’s personalizednutrition program. In some cases, the data is obtained from analyzing a body fluid sample from the user. The body fluid may be blood, plasma, urine, saliva, or stool, for example. The one or more biomarkers can include Vitamin D, Omega-3, magnesium, Omega-3, Vitamin B12, choline, polyphenols, soluble fiber, Vitamin C, iron, ferritin, methyl malonic acid (MMA), high-sensitivity C-reactive protein (hs-CRP), gamma-glutamyl transferase (GGT), cortisol, hemoglobin A1C (HbAlC), cholesterol panel, Apolipoprotein B (ApoB), folate, calcium, or an aspartate transaminase (AST) / alanine transaminase (ALT) ratio, for example.

[0039] In some cases, determining a user’s personalized nutrition program is based on levels of one or more biomarkers of the user, epigenetic data of the user, and one or more genetic dispositions of the user.

[0040] In some cases, the list of biographical questions, the list of symptoms, the list of objectives, the list of nutrients, or the list of foods can be periodically updated.

[0041] A user can use the systems, the methods, the computer-readable media, and the techniques described herein to receive an updated personalization plan at a later date. The computer system can prompt the user to repeat steps the method at a given time interval or when the user at least partially achieves one or more objectives or at least partially alleviates one or more of the symptoms that the user suffers from, he

[0042] In some cases, determining the personalized nutrition program comprises determining a first relative weight of the biographical representation of the user, (ii) determining a second relative weight of the one or more objectives of the user, and (iii) determining a third relative weight of the symptom representation of the user. Determining the nutrition program can be based on a combination of the first, second, and third relative weights. In some cases, the first relative weight of the biographical representation comprises a plurality of weights for each nutrient in the list of nutrients. For example, each user query for the biological profile may be associated with a plurality of weights (e.g., a 1 to 10 score, 1 to 5 score, 1 to 3 score, to provide an example), and each nutrient of the list of nutrient may have a particular weighting for a particular answer; each answer to the query may be associated with a set of particular weights for the list of nutrients, and different query answers may typically have different sets of weights for the list of nutrients.

[0043] In some cases, the biographical representation of the user comprises a plurality of biographical parameters, each biographical parameter comprising a relative weight for each nutrient of a list of nutrients. In some cases, the second relative weight of the one or more objectives comprises a plurality of weights for each nutrient in a list of nutrients. In some cases, each objective comprises a relative weight for each nutrient of the list of nutrients. Forexample, each user query for a particular objective may be associated with a plurality of weights (e.g., a 1 to 10 score, 1 to 5 score, 1 to 3 score, to provide an example), and each nutrient of the list of nutrient may have a particular weighting for a particular answer; each answer to the query may be associated with a set of particular weights for the list of nutrients, and different query answers may typically have different sets of weights for the list of nutrients. In some cases, the third relative weight of the symptom representation comprises a plurality of weights for each nutrient in a list of nutrients. In some cases, the symptom representation comprises a plurality of symptoms, each symptom comprising a relative weight for each nutrient of a list of nutrients. In some cases, the symptom representation may include a symptom profile. For example, each user query for the symptom representation may be associated with a plurality of weights (e.g., a 1 to 10 score, 1 to 5 score, 1 to 3 score, to provide an example), and each nutrient of the list of nutrient may have a particular weighting; each answer to the query may be associated with a set of particular weights for the list of nutrients, and different query answers may typically have different sets of weights for the list of nutrients. Likewise, other queries and / or user profile parameters may have similar weighting associated with particular query answers or user profile parameters.

[0044] The weights described above may be provided by a dietary specialist or nutritionist or other medical or lifestyle professional or specialist. The weights may on occasion be updated, for example, to keep up with the latest in nutritional or other science.

[0045] In many embodiments, determining the nutrition program can be based on a combination of the first, second, third, and other relative weights. The combination of the weights may provide a relative ranking of nutrients for the user to prioritize in their diet and / or lifestyle. Based on these relative rankings (e.g., top nutrients, for example, top 3-5 nutrients, the system may automatically provide diet and / or lifestyle recommendations for the user. At regular intervals after the recommendations are provided, the user may check with the system for compliance to the recommendations and update their query answers and / or personal parameters. The dietary specialist or nutritionist or other medical or lifestyle professional or specialist may check user compliance as well, for example, by reviewing whether the user has toggled one or more flags or other indicators with the system, for example. With updates to the user’s query answers and / or personal parameters, the system may provide an updated relative ranking of nutrients as well as updated diet and / or lifestyle recommendations. Over multiple intervals, the progress of the user, including changes in the user’s query answers, personal parameters, relative rankings of nutrients, compliance, and / or system recommendations, may be tracked longitudinally. With multiple users using thesystem, population data for the aforementioned may be gathered, and trends and / or recommendations for particular demographics may be determined.

[0046] FIG. 1 shows a method 100 for providing a questionnaire to a user and generating a personalized nutritional plan as provided herein. The questionnaire can be implemented using the systems, the methods, the computer-readable media, and the techniques provided herein. A system or device includes one or more processors for executing machine-readable code implementing the method. The machine-readable code can be stored in a memory location of the system or device. In some cases, the machine-readable code is stored in remote system and, in some situations, executed in the remote system. In a first step 101, a system implementing the questionnaire presents a user with a first query to establish a biographical representation of the user. In a second step 102, a system implementing the questionnaire presents a user with a second query to establish one or more objectives of the user. In a third step 103, a system implementing the questionnaire presents a user with a third query to establish a symptom representation of the user. The questions can be presented to the user using graphical, textual, audio, and / or video elements, such as a video of an actor or animation asking the user a question. These elements can be provided to the user using an interactive display of a system or device implementing the method 100. Next, the user inputs a response into the system implementing the method 100 to respond to the first, second, and third queries. The user can input the response using an interactive display or other input device of the system, such as a touch screen (e.g., capacitive touch screen, resistive touch screen), voice activation and / or gestures. Next, in step 105, the system interprets the user’s response to determine a nutrition program emphasizing one or more key nutrients to aid in one or more of (i) achieving the one or more objectives of the user or (ii) alleviating one or more of the symptoms that the user suffers from. Next, in step 106, the system may display the user a nutrition program comprising the one or more key nutrients. Optionally, the system may determine whether there are additional questions to present to the user in the questionnaire. Steps 101-103 can then be repeated as necessary to present additional questions to the user.

[0047] FIG. 2 shows an additional step 107 of obtaining a genetic report of the user. The genetic report can be used in step 105 to confirm and / or supplement the personalized nutrition program.

[0048] FIG. 3 shows an additional step 108 of obtaining omic data of the user. The omic data can be used in step 105 to confirm and / or supplement the personalized nutrition program.

[0049] FIG. 4 shows an additional step 109 of obtaining data for levels of one or more biomarkers of the user. The levels of biomarkers can be used in step 105 to confirm and / or supplement the personalized nutrition program.

[0050] FIG. 5 shows a method where a genetic report, omic data, and levels of biomarkers are used in step 105 to confirm and / or supplement the personalized nutrition program.

[0051] FIG. 6 shows an additional step 120, where after the plan is implemented and one or more objectives are achieved and / or one or more symptoms of the user are at least partially relieved, the user retakes the questionnaire in step 125. The user may respond differently to the queries during subsequent retakes, and therefore, the one or more key nutrients may be modified from the initial nutrition program. A user may retake the questionnaire as often as desired.

[0052] FIG. 7 shows an additional step 130, where after the plan is implemented, the user is prompted to retake the questionnaire at a given time interval. The user may retake the questionnaire in step 135. The user may respond differently to the queries during subsequent retakes, and therefore, the one or more key nutrients may be modified from the initial nutrition program. A user may retake the questionnaire at a given time interval, which can be prompted by the computer system.

[0053] FIG. 8 shows an additional step 140, where a professional reviews the personalized nutrition program. A professional can be a nutritionist, dietician, clinician, or doctor, for example. The professional can update the computer algorithm periodically in step 145. Updating the algorithm may include updating the relevant weights attributed to the queries and the key nutrients. A professional may update the algorithm periodically or at a given time interval, which can be prompted by the computer system.

[0054] FIG. 9 shows an additional step 150, where a professional reviews the personalized nutrition program. A professional can be a nutritionist, dietician, clinician, or doctor, for example. The professional can update the one or more queries in steps 101, 102, and 103 periodically in step 155. Updating the queries may include adding, removing, or modifying questions presented in the queries. A professional may update the queries periodically or at a given time interval, which can be prompted by the computer system.

[0055] Although the above steps show various methods of determining a personalized nutrition program for a user in accordance with embodiments, a person of ordinary skill in the art will recognize many variations based on the teachings described herein. The steps may be completed in a different order. Steps may be added or deleted. Some of the steps may comprise sub-steps. Many of the steps may be repeated as often as beneficial to the user.Computer Systems

[0056] The present disclosure provides computer systems that are programmed to implement methods of the disclosure. FIG. 10 shows a computer system 601 that is programmed or otherwise configured to, for example, implement a trained machine learning classifier to determine a personalized nutrition program for a user based on the user’s answers to one or more queries.

[0057] The computer system 601 can regulate various aspects of analysis, calculation, and generation of the present disclosure, such as, for example, implement a trained machine learning classifier to implement a trained machine learning classifier to determine a personalized nutrition program for a user based on the user’s answers to one or more queries. The computer system 601 can be an electronic device of a user or a computer system that is remotely located with respect to the electronic device. The electronic device can be a mobile electronic device.

[0058] The computer system 601 includes a central processing unit (CPU, also “processor” and “computer processor” herein) 605, which can be a single core or multi core processor, or a plurality of processors for parallel processing. The computer system 601 also includes memory or memory location 610 (e.g., random-access memory, read-only memory, flash memory), electronic storage unit 615 (e.g., hard disk), communication interface 620 (e.g., network adapter) for communicating with one or more other systems, and peripheral devices 625, such as cache, other memory, data storage and / or electronic display adapters. The memory 610, storage unit 615, interface 620 and peripheral devices 625 are in communication with the CPU 605 through a communication bus (solid lines), such as a motherboard. The storage unit 615 can be a data storage unit (or data repository) for storing data. The computer system 601 can be operatively coupled to a computer network (“network”) 630 using the communication interface 620. The network 630 can be the Internet, an internet and / or extranet, or an intranet and / or extranet that is in communication with the Internet.

[0059] The network 630 In some embodiments is a telecommunication and / or data network. The network 630 can include one or more computer servers, which can enable distributed computing, such as cloud computing. For example, one or more computer servers may enable cloud computing over the network 630 (“the cloud”) to perform various aspects of analysis, calculation, and generation of the present disclosure, such as, for example, implementing a trained machine learning classifier to determine a personalized nutrition program for a user based on the user’s answers to one or more queries as described herein. Such cloudcomputing may be provided by cloud computing platforms such as, for example, Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform, and IBM cloud. The network 630, In some embodiments using the computer system 601, can implement a peer-to- peer network, which may enable devices coupled to the computer system 601 to behave as a client or a server.

[0060] The CPU 605 may comprise one or more computer processors and / or one or more graphics processing units (GPUs). The CPU 605 can execute a sequence of machine-readable instructions, which can be embodied in a program or software. The instructions may be stored in a memory location, such as the memory 610. The instructions can be directed to the CPU 605, which can subsequently program or otherwise configure the CPU 605 to implement methods of the present disclosure. Examples of operations performed by the CPU 605 can include fetch, decode, execute, and writeback.

[0061] The CPU 605 can be part of a circuit, such as an integrated circuit. One or more other components of the system 601 can be included in the circuit. In some embodiments, the circuit is an application specific integrated circuit (ASIC). The storage unit 615 can store files, such as drivers, libraries and saved programs. The storage unit 615 can store user data, e.g., user preferences and user programs. The computer system 601 in some embodiments can include one or more additional data storage units that are external to the computer system 601, such as located on a remote server that is in communication with the computer system 601 through an intranet or the Internet.

[0062] The computer system 601 can communicate with one or more remote computer systems through the network 630. For instance, the computer system 601 can communicate with a remote computer system of a user. Examples of remote computer systems include personal computers (e.g., portable PC), slate or tablet PC’s (e.g., Apple® iPad, Samsung® Galaxy Tab), telephones, Smart phones (e.g., Apple® iPhone, Android-enabled device, Blackberry®), or personal digital assistants. The user can access the computer system 101 via the network 630.

[0063] Methods as described herein can be implemented by way of machine (e.g., computer processor) executable code stored on an electronic storage location of the computer system 601, such as, for example, on the memory 610 or electronic storage unit 615. The machine executable or machine readable code can be provided in the form of software. During use, the code can be executed by the processor 605. In some embodiments, the code can be retrieved from the storage unit 615 and stored on the memory 610 for ready access by the processor605. In some situations, the electronic storage unit 615 can be precluded, and machineexecutable instructions are stored on memory 610.

[0064] The code can be pre-compiled and configured for use with a machine having a processer adapted to execute the code or can be compiled during runtime. The code can be supplied in a programming language that can be selected to enable the code to execute in a pre-compiled or as-compiled fashion.

[0065] Embodiments of the systems, the methods, the computer-readable media, and the techniques provided herein, such as the computer system 601, can be embodied in programming. Various aspects of the technology may be thought of as “products” or “articles of manufacture” typically in the form of machine (or processor) executable code and / or associated data that is carried on or embodied in a type of machine readable medium. Machine-executable code can be stored on an electronic storage unit, such as memory (e.g., read-only memory, random-access memory, flash memory) or a hard disk. “Storage” type media can include any or all of the tangible memory of the computers, processors or the like, or associated modules thereof, such as various semiconductor memories, tape drives, or disk drives, which may provide non-transitory storage at any time for the software programming. All or portions of the software may at times be communicated through the Internet or various other telecommunication networks. Such communications, for example, may enable loading of the software from one computer or processor into another, for example, from a management server or host computer into the computer platform of an application server. Thus, another type of media that may bear the software elements includes optical, electrical and electromagnetic waves, such as used across physical interfaces between local devices, through wired and optical landline networks and over various air-links. The physical elements that carry such waves, such as wired or wireless links, optical links or the like, also may be considered as media bearing the software. As used herein, unless restricted to non- transitory, tangible “storage” media, terms such as computer or machine “readable medium” refer to any medium that participates in providing instructions to a processor for execution.

[0066] Hence, a machine readable medium, such as computer-executable code, may take many forms, including a tangible storage medium, a carrier wave medium or physical transmission medium. Non-volatile storage media include, for example, optical or magnetic disks, such as any of the storage devices in any computer(s) or the like, such as may be used to implement the databases, etc. shown in the drawings. Volatile storage media include dynamic memory, such as main memory of such a computer platform. Tangible transmission media include coaxial cables; copper wire and fiber optics, including the wires that comprisea bus within a computer system. Carrier-wave transmission media may take the form of electric or electromagnetic signals, or acoustic or light waves such as those generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer- readable media therefore include for example: a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD or DVD-ROM, any other optical medium, punch cards paper tape, any other physical storage medium with patterns of holes, a RAM, a ROM, a PROM and EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave transporting data or instructions, cables or links transporting such a carrier wave, or any other medium from which a computer may read programming code and / or data. Many of these forms of computer readable media may be involved in carrying one or more sequences of one or more instructions to a processor for execution.

[0067] The computer system 601 can include or be in communication with an electronic display 635 that comprises a user interface (UI) 640 for providing, for example, a visual display displaying a personalized nutrition program. Examples of UIs include, without limitation, a graphical user interface (GUI) and web-based user interface.

[0068] The systems, the methods, the computer-readable media, and the techniques of the present disclosure can be implemented by way of one or more algorithms. An algorithm can be implemented by way of software upon execution by the central processing unit 605. The algorithm can, for example, determine a personalized nutrition program for a user based on the user’s answers to one or more queries.Machine Learning Techniques

[0069] Population data may be input to a machine learning model and a user may query the model to identify trends and associations for a particular demographic (for example, any combination of age range, sex, height range, weight range, ethnicity, ancestry, diet, top nutrients, etc.). These trends and associations may be reviewed by a nutritional or other health professional for updates to diet and lifestyle recommendations by the system for particular top nutrients or the demographic, as well as possible updates to the weightings for the query answers.

[0070] As disclosed herein, various machine learning (ML) techniques may be employed via the systems, the methods, the computer-readable media, and the techniques provided. In some cases, ML may generally involve identifying and recognizing patterns in existing data in order to facilitate making predictions for subsequent data. ML may include a ML model (which may include, for example, a ML algorithm). Machine learning, whether analytical or statistical in nature, may provide deductive or abductive inference based on real or simulateddata. The ML model may be a trained model. ML techniques may comprise one or more supervised, semi-supervised, self-supervised, or unsupervised ML techniques. For example, an ML model may be a trained model that is trained through supervised learning (e.g., various parameters are determined as weights or scaling factors). ML may comprise one or more of regression analysis, regularization, classification, dimensionality reduction, ensemble learning, meta learning, association rule learning, cluster analysis, anomaly detection, deep learning, or ultra-deep learning. ML may comprise: k-means, k-means clustering, k-nearest neighbors, learning vector quantization, linear regression, non-linear regression, least squares regression, partial least squares regression, logistic regression, stepwise regression, multivariate adaptive regression splines, ridge regression, principal component regression, least absolute shrinkage and selection operation (LASSO), least angle regression, canonical correlation analysis, factor analysis, independent component analysis, linear discriminant analysis, multidimensional scaling, non-negative matrix factorization, principal components analysis, principal coordinates analysis, projection pursuit, Sammon mapping, t-distributed stochastic neighbor embedding, AdaBoosting, boosting, gradient boosting, bootstrap aggregation, ensemble averaging, decision trees, conditional decision trees, boosted decision trees, gradient boosted decision trees, random forests, stacked generalization, Bayesian networks, Bayesian belief networks, naive Bayes, Gaussian naive Bayes, multinomial naive Bayes, hidden Markov models, hierarchical hidden Markov models, support vector machines, encoders, decoders, auto-encoders, stacked auto-encoders, perceptrons, multi-layer perceptrons, artificial neural networks, feedforward neural networks, convolutional neural networks, recurrent neural networks, long short-term memory, deep belief networks, deep Boltzmann machines, deep convolutional neural networks, deep recurrent neural networks, large language models, vision transformers, or generative adversarial networks.

[0071] Training the ML model may include, in some cases, selecting one or more untrained data models to train using a training data set. The selected untrained data models may include any type of untrained ML models for supervised, semi-supervised, self-supervised, or unsupervised machine learning. The selected untrained data models may be specified based upon input (e.g., user input) specifying relevant parameters to use as predicted variables or other variables to use as potential explanatory variables. For example, the selected untrained data models may be specified to generate an output (e.g., a prediction) based upon the input. Conditions for training the ML model from the selected untrained data models may likewise be selected, such as limits on the ML model complexity or limits on the ML modelrefinement past a certain point. The ML model may be trained (e.g., via a computer system such as a server) using the training data set. In some cases, a first subset of the training data set may be selected to train the ML model. The selected untrained data models may then be trained on the first subset of training data set using appropriate ML techniques, based upon the type of ML model selected and any conditions specified for training the ML model. In some cases, due to the processing power requirements of training the ML model, the selected untrained data models may be trained using additional computing resources (e.g., cloud computing resources). Such training may continue, in some cases, until at least one aspect of the ML model is validated and meets selection criteria to be used as a predictive model.

[0072] In some cases, one or more aspects of the ML model may be validated using a second subset of the training data set (e.g., distinct from the first subset of the training data set) to determine accuracy and robustness of the ML model. Such validation may include applying the ML model to the second subset of the training data set to make predictions derived from the second subset of the training data. The ML model may then be evaluated to determine whether performance is sufficient based upon the derived predictions. The sufficiency criteria applied to the ML model may vary depending upon the size of the training data set available for training, the performance of previous iterations of trained models, or user-specified performance requirements. If the ML model does not achieve sufficient performance, additional training may be performed. Additional training may include refinement of the ML model or retraining on a different first subset of the training dataset, after which the new ML model may again be validated and assessed. When the ML model has achieved sufficient performance, in some cases, the ML may be stored for present or future use. The ML model may be stored as sets of parameter values or weights for analysis of further input (e.g., further relevant parameters to use as further predicted variables, further explanatory variables, further user interaction data, etc.), which may also include analysis logic or indications of model validity in some instances. In some cases, a plurality of ML models may be stored for generating predictions under different sets of input data conditions. In some embodiments, the ML model may be stored in a database (e.g., associated with a server).EXAMPLES

[0073] The examples and embodiments described herein are for illustrative purposes only and various modifications or changes suggested to persons skilled in the art are to be included within the spirit and purview of this application and scope of the appended claims.

[0074] As displayed in FIG. 1, the method described herein may begin with a user being presented a first query 101. The first query may be used to establish a biographical representation of the user. The first query may include a list of biographical questions. The user may be asked their name, zip code, age, gender, or sex. The user may be asked whether about their medical history, including medications taken, recent surgeries, or whether they suffer from any conditions or diseases. The user may be asked questions about their lifestyle, including exercise or activity level, alcohol consumption, or special diet or dietary restrictions. The user may be asked about their physical attributes, including height, weight, waist circumference, body mass index, or skin color. The user may be asked questions about their current diet and how often they eat certain foods. For example, a user can be asked how often they consume water, red meat, leafy greens, nuts / seeds, whole eggs, fatty fish, green or black tea, berries, apples, citrus fruits, juice, onions, garlic, red wine, grapes, dark chocolate, herbs, spices, and / or olive oil. Each response may be associated with one or more key nutrients. For example, if a user indicates that they rarely not eat fatty fish, the computer system may flag Omega-3 as an important nutrient for the user. The importance of a nutrient may depend on a user’s answer to any given question. For example, if a user occasionally eats fatty fish, the computer system may rank Omega-3 as a moderate priority, and if a user never eats fatty fish, the computer system may rank Omega-3 as a high priority. The importance or priority of a nutrient may be represented by a number scale.

[0075] Next, the user may be presented a second query 102. The second query may be used to establish one or more objectives of the user. One or more objectives may be presented to the user using a graphical interface, and the user may be prompted to choose the one or more objectives that are the highest priority for the user. A user may be prompted to select three goals from the list of goals. Alternatively, the user may rank the one or more objectives in order of priority or importance. Objectives may include heart health, immune health, aging health (cancer, sarcopenia, osteoporosis), brain health (cognitive decline, dementia), metabolic health (weight control, diabetes), and / or gut health, for example. Each objective may be associated with one or more key nutrients. For example, if a user indicates that heart health is their highest priority, the computer system may flag Omega-3 as an important nutrient for the user.

[0076] Next, the user may be presented a third query 103. The third query may be used to identify one or more symptoms that the user is suffering from or concerned with. A list of symptoms may be presented to the user using a graphical interface, and the user may be prompted to choose the symptoms that apply to the user. A user may be prompted to selectthe top three symptoms from the list of symptoms. Symptoms may include frequent sickness (cold, flu, infections), brain fog (memory, concentration), mood issues (anxiety, depression), premenstrual syndrome (PMS), constipation, fatigue, skin aging, poor appetite control, poor exercise recovery, insomnia / sleep issues, difficulty managing stress, and / or joint pain, for example. Each symptom may be associated with one or more key nutrients. For example, if a user indicates that they suffer from frequent sickness, the computer system may flag Vitamin C as an important nutrient for the user. The importance or priority of a nutrient may be represented by a number scale.

[0077] After responses to the three queries are received from the user in 104, a computer system may be used in step 105 to determine a personalized nutrition program for the user. The personalized nutrition program can emphasize one or more key nutrients to achieve the one or more objectives of the user or alleviate one or more of the symptoms the user suffers from. The one or more key nutrients may be selected from a list of nutrients. The list of nutrients may comprise Vitamin A, Vitamin B, Vitamin B 12, thiamin, riboflavin, folic acid, Vitamin C, Vitamin D, Vitamin E, Vitamin K, calcium, iron, chloride, phosphorous, potassium, magnesium, choline, polyphenols, soluble fiber, among others. As discussed with regards to steps 101, 102, and 103, each of the user’s responses may have a weight associated with one or more nutrients in the list of nutrients. The computer system can weigh the importance of all nutrients based on the user’s responses in steps 104 and determine the top nutrients from the list of nutrients. The computer system may output the three most important nutrients. The personalized nutrition program may list these three nutrients. Additionally, the personalized nutrition program may recommend foods that will provide the nutrients.

[0078] As displayed in FIGs. 2-5, a genetic report, omic data, and / or one or more biomarker levels can be used to supplement and / or confirm the personalized nutrition program. The genetic report of the user, omic data, and / or one or more biomarker levels can also be associated with one or more nutrients. A genetic report of the user may show variations in the user’s genes that explain how the user’s body responds to certain nutrients. Omic data may include an epigenetics test, which can show the user’s biological age and rate of aging. Biomarker levels may include current levels of nutrients in the user’s body.

[0079] While preferred embodiments of the present invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions will now occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may beemployed in practicing the invention. It is intended that the following claims define the scope of the invention and that methods and structures within the scope of these claims and their equivalents be covered thereby.

[0080] In another example application, the present disclosure may be applied to dining at restaurants. The menu of the restaurant may be obtained by a computer system disclosed herein. For example, the menu may be obtained via a user taking a photograph (e.g., via a smartphone camera) of the menu. In another example, the menu may be obtained digitally (e.g., from the restaurant’s website, digital services that compile restaurant data, etc.). In another example, the menu itself may include a code (e.g., a barcode, a QR code, a UPC code, etc.) that, when scanned, provides a listing of the food on the menu. The nutrients or ingredients of food on the menu may be obtained directly (e.g., via being listed out) or may be inferred (e.g., via predicting common or likely ingredients in a food item). Leveraging the present disclosure, the user may obtain a recommendation for food to order from the menu. For example, the user may receive a recommended food. In another example, the user may receive a recommended ranked list of food. In another example, the user may additionally receive recommended proposed substitutes or removals to request when ordering certain food from the menu. FIGs. 11A and 11B show examples of user interfaces 1100 A and 1100B presenting a meal planner personalized for a nutrition program. The meal planner of 1100A and 1100B may leverage the algorithms disclosed herein to will filter the food / recipes to show food / recipes that improve user health. The meal planner then allows the user to specifically choose meals (e.g., for the week) based on the user’s personal nutritional needs. The user interfaces 1100A and 1100B, or similar user interfaces, may be used with dining in restaurants. For example, the user interfaces 1100A and 1100B may suggest meals to order at the restaurant.

[0081] In another example application, the present disclosure may be applied to shopping. The stock of food at a store (e.g., convenience store, grocery store, market, etc.) may be obtained by a computer system disclosed herein. For example, the stock of food may be obtained via a user taking a photograph (e.g., via a smartphone camera) of food items (e.g., of the food item itself, of a code associated with the food item, of the packaging of the food item, of a written description of the food item, etc.). In another example, the stock of food may be obtained digitally (e.g., from the store’s website, from the store’s stock database, digital services that compile store data, etc.). The nutrients or ingredients of food in the stock of food may be obtained directly (e.g., via being listed out) or may be inferred (e.g., via predicting common or likely ingredients in a food item). Leveraging the present disclosure,the user may obtain a recommendation for food to buy (or not to buy) from the store. For example, the user may receive a recommended food. In another example, the user may receive a recommended ranked list of food. These recommendations may be presented, in one example, to the user while the user is collecting food items while shopping. In another example, these recommendations may be presented to the user while the user is checking out. In such example, the user may be presented with a recommendation not to buy a food item or to buy an alternate / additional food item in response to the user scanning a food item at checkout. FIGs. 11 A and 11B show examples of user interfaces 1100 A and 1100B presenting a meal planner personalized for a nutrition program. The meal planner of 1100A and 1100B may leverage the algorithms disclosed herein to will filter the food / recipes to show food / recipes that improve user health. The meal planner then allows the user to specifically choose meals (e.g., for the week) based on the user’s personal nutritional needs. The user interfaces 1100A and 1100B, or similar user interfaces, may be used with shopping. For example, the user interfaces 1100A and 1100B may suggest meals or ingredients to buy at a store.

[0082] In another example application, the present disclosure may be applied to cooking. The cooking ingredients (e.g., base ingredients, whole food items, whole meal items, etc.) may be obtained by a computer system disclosed herein. For example, the cooking ingredients may be obtained via a user taking a photograph (e.g., via a smartphone camera) of a refrigerator, a freezer, a pantry, etc. In another example, the menu may be obtained digitally (e.g., from a smart refrigerator, from shopping receipts or transactions, etc.). The nutrients of the cooking ingredients may be obtained directly (e.g., via being listed out, such as on packaging) or may be inferred (e.g., via predicting common or likely ingredients in a cooking ingredient). Leveraging the present disclosure, the user may obtain a recommendation for food to cook. For example, the user may receive a recommended food to cook. In another example, the user may receive a recommended ranked list of food to cook. In another example, the user may additionally receive recommended proposed substitutes or additions to acquire to cook a certain food. The user may obtain a schedule of food to cook (e.g., for meal preparation), such as for one or more meals in a day, a three day period, a week, a month, etc. FIGs. 11A and 11B show examples of user interfaces 1100 A and 1100B presenting a meal planner personalized for a nutrition program. The meal planner of 1100 A and 1100B may leverage the algorithms disclosed herein to will filter the food / recipes to show food / recipes that improve user health. The meal planner then allows the user to specifically choose meals (e.g., for the week) based on the user’s personal nutritional needs. The user interfaces 1100Aand 1100B, or similar user interfaces, may be used with cooking. For example, the user interfaces 1100A and 1100B may suggest meals to cook.

Claims

CLAIMSWHAT IS CLAIMED IS:

1. A method for developing a nutrition program personalized to a user, the method comprising:(a) causing display of, using a computer system and a graphical display, a first query to said user, wherein a first user response from said user to said first query is used to determine a biographical representation of said user;(b) causing display of, using said computer system and said graphical display, a second query to said user, wherein a second user response to said second query is used to determine one or both of (i) one or more objectives of said user or (ii) a symptom representation of said user;(c) obtaining, using said computer system, based at least in part on said biographical representation and one or both of (i) said one or more objectives or (ii) said symptom representation, a nutrition program corresponding to one or more nutrients; and(d) causing display of, using said computer system and said graphical display, said nutrition program corresponding to said one or more nutrients, wherein said one or more nutrients aid in one or both of (i) achieving said one or more objectives or (ii) addressing one or more symptoms corresponding to said symptom representation.

2. The method of claim 1, wherein said first query asks said user to respond to a list of biographical questions.

3. The method of claim 2, wherein said list of biographical questions comprises one or more questions related to demographic information of said user or a family of said user.

4. The method of claim 3, wherein said demographic information comprises an age of said user.

5. The method of claim 3, wherein said demographic information comprises a sex of said user.

6. The method of claim 3, wherein said demographic information comprises a gender of said user.

7. The method of claim 3, wherein said demographic information comprises a geographical location of said user.

8. The method of claim 3, wherein said demographic information comprises an ancestry of said user.

9. The method of claim 2, wherein said list of biographical questions comprises one or more questions related to a medical history of said user or a family of said user.

10. The method of claim 9, wherein said medical history comprises one or more medications taken by said user.

11. The method of claim 9, wherein said medical history comprises a chronic disease state of said user.

12. The method of claim 2, wherein said list of biographical questions comprises one or more questions related to lifestyle information of said user or family of said user.

13. The method of claim 12, wherein said lifestyle information comprises an eating habit of said user.

14. The method of claim 12, wherein said lifestyle information comprises an exercise habit of said user.

15. The method of claim 12, wherein said lifestyle information comprises an alcohol consumption habit of said user.

16. The method of claim 12, wherein said lifestyle information comprises an activity level of said user.

17. The method of claim 12, wherein said lifestyle information comprises a special diet or dietary restriction of said user.

18. The method of claim 2, wherein said list of biographical questions comprises one or more questions related to one or more physical attributes of said user.

19. The method of claim 18, wherein said one or more physical attributes of said user comprises a skin color of said user.

20. The method of claim 18, wherein said one or more physical attributes of said user comprises a weight of said user.

21. The method of claim 18, wherein said one or more physical attributes of said user comprises a height of said user.

22. The method of claim 18, wherein said one or more physical attributes of said user comprises a waist circumference of said user.

23. The method of claim 18, wherein said one or more physical attributes of said user comprises a skin color of said user.

24. The method of claim 18, wherein said one or more physical attributes of said user comprises a body mass index of said user.

25. The method of claim 1, wherein said second query asks said user to identify said one or more objectives that correspond to one or more health goals from a list of health goals.

26. The method of claim 25, wherein said list of health goals comprises an immune health goal.

27. The method of claim 25, wherein said list of health goals comprises a gastrointestinal or gut health goal.

28. The method of claim 25, wherein said list of health goals comprises an aging health goal.

29. The method of claim 28, wherein said aging health goal comprises prevention of cancer, sarcopenia, or osteoporosis, or a combination thereof.

30. The method of claim 25, wherein said list of health goals comprises a neurological or brain health goal.

31. The method of claim 30, wherein said neurological or brain health goal comprises preventing cognitive decline or dementia.

32. The method of claim 25, wherein said list of health goals comprises a metabolic health goal.

33. The method of claim 32, wherein said metabolic health goal comprises weight or diabetes control.

34. The method of claim 25, wherein said list of health goals comprises a cardiovascular or heart health goal.

35. The method of claim 25, wherein said list of health goals comprises a performance- related goal.

36. The method of claim 25, wherein said one or more health goals comprises a plurality of health goals, and said second query requires said user to rank said plurality of health goals.

37. The method of claim 1, wherein said second query asks said user to identify said symptom representation from a list of symptoms, wherein said symptom representation corresponds to all symptoms that said user suffers from.

38. The method of claim 37, wherein said list of symptoms comprises one or more physical energy or health-related symptoms.

39. The method of claim 38, wherein said one or more physical energy or health-related symptoms comprises fatigue.

40. The method of claim 38, wherein said one or more physical energy or health-related symptoms comprises constipation.

41. The method of claim 38, wherein said one or more physical energy or health-related symptoms comprises skin aging.

42. The method of claim 38, wherein said one or more physical energy or health-related symptoms comprises poor exercise recovery.

43. The method of claim 38, wherein said one or more physical energy or health-related symptoms comprises insomnia or sleep issues.

44. The method of claim 38, wherein said one or more physical energy or health-related symptoms comprises joint pain.

45. The method of claim 38, wherein said one or more physical energy or health-related symptoms comprises premenstrual syndrome (PMS).

46. The method of claim 37, wherein said list of symptoms comprises one or more mentalhealth related symptoms.

47. The method of claim 46, wherein said one or more mental-health related symptoms comprises anxiety.

48. The method of claim 46, wherein said one or more mental-health related symptoms comprises depression.

49. The method of claim 46, wherein said one or more mental-health related symptoms comprises poor appetite control.

50. The method of claim 46, wherein said one or more mental-health related symptoms comprises difficulty managing stress.

51. The method of claim 37, wherein said list of symptoms comprises one or more mentalacuity related symptoms.

52. The method of claim 51, wherein said one or more mental-acuity related symptoms comprises brain fog.

53. The method of claim 37, wherein said list of symptoms comprises one or more immune- related symptoms.

54. The method of claim 51, wherein said one or more immune-related symptoms comprises frequent sickness.

55. The method of claim 1, wherein said nutrition program recommends one or more foods, and wherein said foods provide said determined key one or more nutrients to said user.

56. The method of claim 55, wherein determining said nutrition program comprises selecting, using said computer system and based on said one or more key nutrients, said recommended one or more foods from a list of foods.

57. The method of claim 1, wherein said nutrition program recommends one or more supplements.

58. The method of claim 57, wherein a first supplement of said one or more supplements aids in achieving said one or more health goals of said user.

59. The method of claim 58, wherein a second supplement of said one or more supplements aids in alleviating one or more of said symptoms that said user suffers from.

60. The method of claim 57, wherein determining said nutrition program comprises selecting, using said computer system and based on said one or more key nutrients, said recommended one or more supplements from a list of supplements.

61. The method of claim 1, wherein said one or more nutrients comprise a plurality of nutrients.

62. The method of claim 1, wherein said one or more key nutrients are selected from a list of nutrients.

63. The method of claim 62, wherein said list of nutrients comprises Vitamin B 12, Vitamin D, Omega-3, Magnesium, Choline, Polyphenols, Soluble Fiber, or Vitamin C.

64. The method of claim 62, wherein said list of nutrients comprises Vitamin B 12, Vitamin D, Omega-3, Magnesium, Choline, Polyphenols, Soluble Fiber, and Vitamin C.

65. The method of claim 1, further comprising obtaining a genetic report of said user.

66. The method of claim 65, wherein said obtaining said nutrition program corresponding to said one or more key nutrients at (c) is further based on said genetic report of said user.

67. The method of claim 65, wherein said genetic report of said user comprises epigenetic data of said user.

68. The method of claim 65, wherein said genetic report comprises one or more genetic predispositions of said user.

69. The method of claim 1, further comprising obtaining omic data of said user.

70. The method of claim 1, further comprising obtaining biomarker data for levels of one or more biomarkers of said user.

71. The method of claim 70, wherein said biomarker data is obtained from analyzing a body fluid sample from said user.

72. The method of claim 71, wherein said body fluid comprises blood.

73. The method of claim 71, wherein said body fluid comprises plasma.

74. The method of claim 71, wherein said body fluid comprises urine.

75. The method of claim 71, wherein said body fluid comprises saliva.

76. The method of claim 70, wherein said obtaining said nutrition program corresponding to said one or more key nutrients at (c) is further based on said data for levels of said one or more biomarkers of said user.

77. The method of claim 71, wherein said one or more biomarkers comprise Vitamin D.

78. The method of claim 71, wherein said one or more biomarkers comprise magnesium.

79. The method of claim 71, wherein said one or more biomarkers comprise omega-3.

80. The method of claim 71, wherein said one or more biomarkers comprise choline.

81. The method of claim 71, wherein said one or more biomarkers comprise Vitamin B12.

82. The method of claim 71, wherein said one or more biomarkers comprise polyphenols.

83. The method of claim 71, wherein said one or more biomarkers comprise soluble fiber.

84. The method of claim 71, wherein said one or more biomarkers comprise Vitamin C.

85. The method of claim 1, wherein said obtaining said nutrition program corresponding to said one or more key nutrients at (c) is further based on biomarker data for levels of said one or more biomarkers of said user, epigenetic data of said user, and one or more genetic dispositions of said user.

86. The method of claim 2, further comprising updating, using said computer system, said list of biographical questions periodically.

87. The method of claim 25, further comprising updating, using said computer system, said list of health goals periodically.

88. The method of claim 37, further comprising updating, using said computer system, said list of symptoms periodically.

89. The method of claim 56, further comprising updating, using said computer system, said list of foods periodically.

90. The method of claim 60, further comprising updating, using said computer system, said list of supplements periodically.

91. The method of claim 62, further comprising updating, using said computer system, said list of nutrients periodically.

92. The method of claim 1, further comprising repeating operations (a)-(d) to obtain an updated nutrition program of said user.

93. The method of claim 92, wherein said computer system prompts said user to cause said repetition of operations (a)-(e) at a given time interval.

94. The method of claim 1, further comprising repeating operations (a)-(e) when said user at least partially achieves said one or more objectives or at least partially alleviates said one or more of said symptoms that said user suffers from.

95. The method of claim 1, wherein said causing display of said second query to said user at (b) comprises determining both said one or more objectives of said user and said symptom representation of said user, and wherein obtaining said nutrition program corresponding to said one or more nutrients at (c) comprises (i) determining a first relative weight of said biographical representation of said user, (ii) determining a secondrelative weight of said one or more objectives of said user, and (iii) determining a third relative weight of said symptom representation of said user, and wherein determining said nutrition program is based on a combination of said first relative weight, said second relative weight, and said third relative weight.

96. The method of claim 95, wherein said first relative weight of said biographical representation comprises a plurality of weights for each nutrient in a list of nutrients.

97. The method of claim 96, wherein said biographical representation of said user comprises a plurality of biographical parameters, each biographical parameter comprising a relative weight for each nutrient of said list of nutrients.

98. The method of claim 95, wherein said second relative weight of said one or more objectives comprises a plurality of weights for each nutrient in a list of nutrients.

99. The method of claim 98, wherein said one or more objectives comprises a plurality of health goals, each health goal comprising a relative weight for each nutrient of said list of nutrients.

100. The method of claim 95, wherein said third relative weight of said symptom representation comprises a plurality of weights for each nutrient in a list of nutrients.

101. The method of claim 100, wherein said symptom representation comprises a plurality of symptoms, each symptom comprising a relative weight for each nutrient of said list of nutrients.

102. The method of claim 1, further comprising obtaining a plurality of food options.

103. The method of claim 102, wherein said nutrition program comprises a recommendation of one or more food options from the plurality of food options to the user.

104. The method of claim 102 or 103, wherein a restaurant menu comprises said plurality of food options.

105. The method of claim 104, wherein said recommendation of said one or more food options comprise a recommendation to order said one or more food options at a restaurant corresponding to said restaurant menu.

106. The method of claim 102 or 103, wherein a store comprises said plurality of food options.

107. The method of claim 106, wherein said recommendation of said one or more food options comprise a recommendation to purchase said one or more food options at said store.

108. The method of claim 102 or 103, wherein one or more of a refrigerator, a freezer, or a pantry comprises said plurality of food options.

109. The method of claim 108, wherein said recommendation of said one or more food options comprise a recommendation to cook said one or more food options at a kitchen corresponding to said one or more of said refrigerator, said freezer, or said pantry.

110. A system for developing a nutrition program personalized to a user, said system comprising: a computer system operatively coupled to a graphical display, wherein said computer system comprises machine-executable code that, upon execution by one or more computer processors, implements any one of the methods of claims 1 to 110.

111. A system for developing a nutrition program personalized to a user, said system comprising: a computer system operatively coupled to a graphical display, wherein said computer system comprises machine-executable code that, upon execution by one or more computer processors, implements operations comprising:(a) presenting a first query to said user, wherein a first user response from said user to said first query is used to determine a biographical representation of said user;(b) presenting a second query to said user, wherein a second user response to said second query is used to determine one or both of (i) one or more objectives of said user, or (ii) a symptom representation of said user;(c) determining, based at least in part on said biographical representation and one or both of (i) said one or more objectives or (ii) said symptom representation, a nutrition program corresponding to one or more nutrients; and(e) displaying said nutrition program corresponding to said one or more nutrients, wherein said one or more nutrients aid in one or both of (i) achieving said one or more objectives of said user or (ii) addressing one or more symptoms corresponding to said symptom representation.

Images