Meal plan recommendation system based on patient
A system and method for personalized diet recommendations based on patient symptoms and preferences address the challenge of treating symptoms in patients with medical conditions, enhancing treatment response and quality of life.
Patent Information
- Application Number
- JP2025058673
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2019-08-12
- Filing Date
- 2025-03-31
- Publication Date
- 2025-07-01
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
Patients with medical conditions often experience symptoms that make it difficult to eat a normal diet, and treatments like chemotherapy interfere with food intake, necessitating personalized nutritional interventions that vary based on individual symptoms and treatment protocols.
A system and method that identifies user information, including symptoms and dietary requirements, to recommend personalized recipes tailored to individual needs, considering symptoms, treatment, diagnosis, and preferences, using a database to match recipes with dietary and recipe requirements.
Enhances treatment response, adherence, reduces hospitalizations, and improves quality of life by providing personalized nutritional interventions that address specific patient symptoms and preferences.
Smart Images
Figure 2025098243000001_ABST
Abstract
Description
Technical Field
[0001]
Background Art
[0002]
[0001] Patients diagnosed with a medical condition (e.g., cancer, digestive condition) often experience one or more symptoms that make it difficult to eat a normal diet. Further, to treat these medical conditions, patients may undergo one or more treatments (e.g., chemotherapy, surgery), which may interfere with the ability to eat certain foods.
Summary of the Invention
[0003]
[0002] The present disclosure presents novel and innovative methods and systems for personalized diet plan recommendations for patients. In one embodiment, a method is provided that includes identifying user information indicative of symptoms affecting the user and identifying dietary requirements based on those symptoms. The method may further include identifying recipe requirements based on the dietary requirements and presenting recipe recommendations to the user based on the recipe requirements.
[0004]
[0003] In another embodiment, identifying user information further includes one or both of receiving from the user user information indicative of the symptom and identifying previously received user information indicative of the symptom.
[0005]
[0004] In yet another embodiment, the method further includes identifying a plurality of recipes in a recipe selection database that comply with the recipe requirements, selecting at least one selected recipe from the plurality of recipes, and including the at least one selected recipe in the recipe recommendation.
[0006]
[0005] In a further embodiment, the at least one selected recipe is selected from the plurality of recipes according to user preferences related to the user information.
[0007]
[0006] In yet another embodiment, the method includes receiving an initial recipe from a recipe database, extracting a list of ingredients and associated tags from the initial recipe, and generating nutritional information and cooking instructions based on the list of ingredients and associated tags.
[0008]
[0007] In another embodiment, the method further includes combining the nutritional information and cooking instructions with the list of ingredients and associated tags to form a generated recipe.
[0009]
[0008] In yet another embodiment, the method further includes storing the generated recipe in a recipe selection database.
[0010]
[0009] In a further embodiment, the dietary requirement identifies (i) a recipe or (ii) a type of food attribute related to alleviating or resolving the condition.
[0011]
[0010] In yet another embodiment, the recipe requirement identifies one or more excluded ingredients, included ingredients, excluded ingredient types, included ingredient types, and / or nutritional requirements for compliance with the dietary requirement.
[0012]
[0011] In another embodiment, the condition includes at least one state selected from the group consisting of anorexia, xerostomia, weight loss, mucositis, nausea, dysphagia, constipation, and diarrhea.
[0013]
[0012] In yet another embodiment, a system is provided that includes a processor and a memory. The memory may store instructions that, when executed by the processor, cause the processor to implement a recommendation requirement database that includes at least (i) a diet requirement table storing a plurality of diet requirements related to one or more symptoms and (ii) a recipe requirement table storing a plurality of recipe requirements related to the diet requirements. The memory may further store instructions that, when executed by the processor, cause the processor to implement a user recommendation system configured to identify user information indicating the symptoms affecting the user and to identify diet requirements based on those symptoms within the diet requirement table. The user recommendation system may be further configured to identify recipe requirements within the recipe requirement table based on those diet requirements and to present recipe recommendations to the user based on those recipe requirements.
[0014]
[0013] In a further embodiment, the user recommendation system is configured to identify user information by receiving user information indicating the relevant symptoms from the user and by identifying previously received user information indicating the relevant symptoms.
[0015]
[0014] In yet another embodiment, the memory stores further instructions that, when executed by the processor, cause the processor to further implement a recipe selection database storing a plurality of recipes related to the plurality of recipe requirements. The user recommendation system may be further configured to identify a plurality of recipes compliant with those recipe requirements within the recipe selection database, to select at least one selected recipe from among the plurality of recipes, and to include the at least one selected recipe in the recipe recommendation.
[0016]
[0015] In another embodiment, the at least one selected recipe is selected from among the plurality of recipes according to user preferences related to the user information.
[0017]
[0016] In yet another embodiment, the memory stores further instructions that, when executed by the processor, cause the processor to receive an initial recipe from the recipe database, extract a list of ingredients and associated tags from the initial recipe, and generate nutritional information and cooking instructions based on the list of ingredients and associated tags, and further cause the recipe generation system to be implemented.
[0018]
[0017] In a further embodiment, the recipe generation system is further configured to combine the nutritional information and cooking instructions with the list of ingredients and associated tags to form a generated recipe.
[0019]
[0018] In yet a further embodiment, the recipe generation system is further configured to store the generated recipe in a recipe selection database.
[0020]
[0019] In another embodiment, the plurality of dietary requirements identify (i) a recipe or (ii) a type of food attribute related to alleviating or resolving the condition.
[0021]
[0020] In yet another embodiment, the recipe requirements identify one or more excluded ingredients, included ingredients, excluded ingredient types, included ingredient types, and / or nutritional requirements for conforming to the dietary requirements.
[0022]
[0021] In a further embodiment, a non-transitory computer-readable medium stores instructions that, when executed by the processor, cause the processor to identify user information indicative of a condition affecting the user and identify dietary requirements based on the condition. The non-transitory computer-readable medium may store further instructions that, when executed by the processor, cause the processor to identify recipe requirements based on the dietary requirements and present recipe recommendations to the user based on the recipe requirements.
[0023]
[0022] The features and advantages described in this specification are not comprehensive, and in particular, many additional features and advantages will become apparent to those skilled in the art upon considering the drawings and the description. Furthermore, note that the language used in this specification is mainly selected for readability and instruction purposes and does not limit the scope of the subject matter of the present invention.
Brief Description of the Drawings
[0024]
[0023]
Figure 1
Figure 2
Figure 3
Figure 4
Modes for Carrying Out the Invention
[0025]
[0027] Patients diagnosed with a certain condition may have symptoms that can negatively impact the quality of the patient's life and may also negatively impact treatment. Therefore, interventions to address these symptoms, particularly nutritional interventions, have been found to enhance treatment response and adherence, reduce hospitalizations, improve quality of life, and have a positive impact on overall outcomes. However, since patients with similar diagnoses may experience different symptoms, prescribing such nutritional interventions based solely on the patient's diagnosis may not be sufficient to treat the patient's symptoms. The differences in symptoms between patients may be related to the specific treatment protocol the patient is receiving and the patient's unique pathophysiology. Furthermore, even for an individual patient, the symptoms experienced may change over time, for example, as the patient's treatment progresses and / or as the patient's condition or diagnosis changes. Therefore, any nutritional intervention needs to be personalized for each patient to address the specific symptoms the patient is facing. One way to provide this level of personalization is to receive information from the patient regarding the symptoms the patient is currently experiencing and create a recommendation for a nutritional intervention based on the patient's symptoms. In some cases, further personalization may be provided based on additional information such as the patient's diagnosis (e.g., cancer diagnosis), the patient's treatment protocol (e.g., chemotherapy, radiation therapy), the patient's medication history, the patient's allergies, and the patient's food preferences. The recommendation for the nutritional intervention may be provided as a recommended recipe to address the patient's symptoms.
[0026]
[0028] Figure 1 shows a system 100 according to an exemplary embodiment of the present disclosure. The system 100 may be configured to identify recipes that alleviate symptoms experienced by a user (e.g., a patient undergoing treatment). The system 100 includes a user recommendation system 102, a user device 130, a recipe generation system 142, and a recipe database 162.
[0027]
[0029] The user recommendation system 102 includes a recommendation requirement database 104, a recipe selection database 112, recipe recommendation proposals 122, a CPU 126, and a memory 128. The user recommendation system 102 may be configured to receive user information such as user information 132 from the user device 130 and generate a recipe recommendation proposal 122 including at least one recipe 124 compliant with the user information 132. For example, the user information 132 may identify one or both of the user's symptoms 134 and diagnosis 136 (e.g., medical diagnosis) associated with the user device 130. The user device 130 may be implemented as a computing device such as a computer, smartphone, tablet, smartwatch, or other wearable. The user device 130 may also be implemented as a voice assistant configured to receive, for example, a voice request from the user and process the request locally on a computer device proximate to the user or on a remote computing device (e.g., at a remote computing server).
[0028]
[0030] As will be further described below, the recommended requirement database 104 stores a diet requirement table 106, a symptom table 108, and a recipe requirement table 110. In certain implementations, the symptom table 108 may be optional. For example, in certain implementations, the recommended requirement database 104 may store the diet requirement table 106 and the recipe requirement table 110, and may not store the symptom table 108. The diet requirement table 106 may store a plurality of diet requirements associated with a certain symptom. For example, as shown in the exemplary table 200 of FIG. 2, the diet requirement table 106 may store the relationship between symptoms 202, 204 and one or more diet requirements 206, 208, 210. The diet requirements 206, 208, 210 may specify requirements for assisting in alleviating or resolving the associated symptoms 202, 204. Table 1 below shows an exemplary diet requirement table 106. The numbered association rules each represent a separate diet requirement 206, 208, 210, and may be stored in association with the corresponding symptoms 202, 204. Symptoms 3 and 4 represent symptom templates, and rules based on the symptoms may be entered herein, similar to the rules for anorexia and dysphagia shown in the table.
Table 1
[0029]
[0031] The symptom table 108 may store a plurality of symptoms related to a certain diagnosis. For example, as shown in the exemplary table 200 of FIG. 2, the symptom table 108 may store the relationships between diagnoses 212, 214 and one or more symptoms 202, 204, 205. The symptoms 202, 204, 205 may be general or non-general relationships with their respective diagnoses 212, 214 that can assist in generating the recipe recommendation 122 when the user provides only the diagnosis. In one implementation, the symptom table 108 may be used to determine one or more symptoms 202, 204, 205 that the user may be experiencing with respect to the provided diagnosis information. For example, if the user provides only the diagnosis, the symptom table 108 may be used to predict the symptoms 202, 204, 205 that the user may be experiencing. In other cases where the user provides both diagnosis and symptom information, the symptom table may be used to predict additional symptoms 202, 204, 205 that the user may be experiencing. In yet another example, the recommendation requirement database 104 may not include the symptom table 108. In such an example, the user may be requested to provide one or more symptoms 202, 204, 205 for further processing.
[0030]
[0032] The recipe requirement table 110 may store information about certain recipe requirements. For example, as shown in the exemplary table 200 of FIG. 2, the recipe requirement 110 may store the dietary requirement 206 in association with one or more recipe requirements 216, 218, 220. The recipe requirements 216, 218, 220 may include specific foods to be incorporated or excluded according to the associated dietary requirement 206. The recipe requirements 216, 218, 220 may also include other restrictions or requirements for the recipe to comply with dietary requirements (e.g., calorie requirements, caffeine requirements, major nutrient requirements). Table 2 below shows an exemplary recipe requirement table 110. The numbered conditions each represent candidate recipe requirements 216, 218, 220 stored in association with the corresponding dietary requirements 206, 208. Similar to Table 1, the row for food category Y may represent a template for recipe requirements, where rule-based recipe requirements may be entered, similar to the recipe requirements for the hard food and low-calorie foods shown in the table. [Table 2]
[0031]
[0033] As further described below, the user recommendation system 102 may utilize the information stored in the recommendation requirement database 104 to determine which types of recipes are acceptable or desirable for users having the identified symptoms 134, 202, 204 and / or diagnoses 136, 212, 214.
[0032]
[0034] The recipe selection database 112 stores recipes 116, 120 in association with one or more dietary requirements 114, recipe requirements 118, and combinations thereof. For example, in a preferred embodiment, the recipe generation system 142 may add recipes 116, 120 that comply with certain recipe requirements 118 to the recipe selection database 112 and store such associations in the recipe selection database 112. In additional or alternative embodiments, the user recommendation system 102 may identify recipes 116, 120 that comply with certain dietary requirements 114 and store such associations in the recipe selection database 112. In such implementations, certain recipes 116, 120 may be stored in association with both dietary requirements 114 and recipe requirements 118.
[0033]
[0035] The recipe database 162 stores recipes 164, 174 in association with one or more tags 171, 172, 179, 180. Recipes 164, 174 may include information for cooking one or more dishes. Thus, as illustrated, recipes 164, 174 include ingredient lists 166, 176 that identify the ingredients included in each dish. In certain implementations, ingredient lists 166, 176 may be stored as tags (e.g., tags 171, 179) that identify one or more of the ingredients included in recipes 164, 174. In yet another implementation, tags 171, 179 corresponding to ingredient lists 166, 176 may provide additional information (e.g., an ingredient category or food attribute related to the ingredients of ingredient lists 166, 176, as further discussed below in relation to tags 172, 180). Recipes 164, 174 may store photos 168, 178 of the finished or cooking dishes. Also, certain recipes 164 may include nutritional information 170 for that recipe. Tags 172, 180 may identify one or more categories or classifications corresponding to each recipe 164, 174. For example, tags 172, 180 may include one or more of vegetarian, high protein, low carbohydrate, gluten free, low calorie, hard food, soft food, along with indicators of recipe requirements 118 (e.g., a restriction or inclusion of a certain food) that recipes 164, 174 comply with.
[0034]
[0036] The recipe generation system 142 may be configured to generate a recipe based on information obtained from the recipe database 162. For example, the recipe generation system 142 may extract limited information from recipes 164, 174, and generate or obtain the remaining information to generate a recipe for inclusion in the recipe selection database 112. In such an example, the recipe generation system 142 may receive from the recipe database 162 a recipe (e.g., recipe 164) with ingredient lists 166 and one or more associated tags 171, 172. Specifically, the recipe generation system 142 may extract limited information from the recipe database 162 according to tags 171, 172, 179, 180 associated with recipes 164, 174. For example, when collecting recipes that comply with the recipe requirement 118 of including a soft food, the recipe generation system 142 may search the recipe database 162 for recipes with tags 171, 172, 179, 180 indicating the inclusion of soft food. Continuing with this example, recipe 164 may be a recipe for banana smoothie, and thus, tag 172 may indicate that recipe 164 includes soft food. In an implementation where ingredient lists 166, 176 are implemented as tags, the recipe generation system 142 may search the recipe database 162 for recipes 164, 174 with tags 171, 169 indicating ingredients that comply with the recipe requirement 118. Then, the recipe generation system 142 may extract information from recipes with matching tags such as the extracted ingredient list 150 and the extracted tags 152. Then, the recipe generation system 142 may generate or obtain nutritional information 154 and cooking instructions 156 for that recipe. The nutritional information 154 and the cooking instructions 156 may be generated based on the extracted ingredient list 150 and / or the extracted tags 152 without relying on further information from the recipe database 162. In a preferred embodiment, the recipe generation system 142 may generate or obtain nutritional information 154 and cooking instructions 156 for each generated recipe, and optionally, may also generate or obtain additional information such as a photo or a description of the recipe for a certain generated recipe.After generation, the recipe generation system 142 may store the generated recipe in the recipe selection database 112 as recipes 116, 120, associated with one or more recipe requirements 118 to which the generated recipe conforms. Additionally or alternatively, the recipe generation system 142 may store the generated recipe in the recipe selection database 112 as recipes 116, 120, associated with one or more dietary requirements 114 to which the generated recipe conforms.
[0035]
[0037] The user recommendation system 102, the user device 130, the recipe generation system 142, and the recipe database 162 may communicate via one or more networks such as a local network and / or the Internet. For example, the user recommendation system 102, the user device 130, the recipe generation system 142, and the recipe database 162 may communicate via one or more wired (e.g., Ethernet (registered trademark)) or wireless (e.g., Wi-Fi, Bluetooth (registered trademark), cellular network) communication links.
[0036]
[0038] One or more of the user recommendation system 102, the user device 130, the recipe generation system 142, and the recipe database 162 may be implemented by a computer system. For example, the CPUs 126, 138, 158 and memories 128, 140, 160 may implement one or more features of the user recommendation system 102, the user device 130, and the recipe generation system 142. For example, when executed by the CPUs 126, 138, 158, the memories 128, 140, 160 may include instructions that cause the CPUs 126, 138, 158 to perform one or more operational features of the user recommendation system 102, the user device 130, and / or the recipe generation system 142. Similarly, although not shown, one or more functions of the recipe database 162 may be implemented by a CPU and / or a memory.
[0037]
[0039] FIG. 3 shows a method 300 according to an exemplary embodiment of the present disclosure. The method 300 may be performed to receive and process user information 132 from the user device 130 and generate recipe recommendations 122. For example, the method 300 may be performed by the user recommendation system 102 to generate recipe recommendations 122. The method 300 may be implemented on a computer system such as the system 100. For example, the method 300 may be implemented by the user recommendation system 102, the user device 130, the recipe generation system 142, and / or the recipe database 162. The method 300 may also be implemented by a set of instructions stored on a computer-readable medium that, when executed by a processor, causes the computer system to perform the method. For example, all or part of the method 300 may be implemented by the CPUs 126, 138, 158 and the memories 128, 140, 160. The following examples are described with reference to the flowchart shown in FIG. 3, but many other methods that perform the operations associated with FIG. 3 may be used. For example, the order of some of the blocks may be changed, some blocks may be combined with other blocks, one or more blocks may be repeated, and some of the described blocks may be optional.
[0038]
[0040] Method 300 begins with the user recommendation system 102 receiving user information 132 indicating a symptom 134 (block 302). For example, the user recommendation system 102 may receive the user information 132 from the user device 130. The symptom 134 may identify one or more symptoms that the user associated with the user device 130 is currently experiencing. For example, the user may have been diagnosed with a particular disease or medical condition, and the symptoms may result from that medical condition and / or the treatment associated with that medical condition. Specifically, the user may have been diagnosed with lower gastrointestinal cancer and as a result may be suffering from constipation. The user may provide the symptom 134 in order to receive a recipe recommendation 122 that includes a recipe 124 useful for alleviating or eliminating the symptom 134. In other implementations, the user information 132 may be received from a healthcare provider, such as a healthcare provider treating the user. The user information 132 may be described as a single symptom or may include two or more symptoms 134. Further, in other implementations, the user information 132 may include a diagnosis 136 that specifies a disease or medical condition corresponding to the associated user for whom the recipe recommendation 122 is to be generated, and in one implementation, as described above, this may be used to identify symptoms 202, 204, 205.
[0039]
[0041] Next, user recommendation system 102 may identify dietary requirements 114, 206, 208, 210 related to user information 132 (block 304). For example, user recommendation system 102 may query diet requirement table 106 using symptoms 134 provided from user information 132 to obtain one or more dietary requirements 206, 208, 210 related to the provided symptoms 134. Continuing with the above example, based on the received symptom 134 indicating constipation, diet requirement table 106 may include dietary requirements 206, 208, 210 that the user incorporate high-fiber foods into the diet. In an implementation where user information 132 includes only diagnosis 136, user recommendation system 102 may identify one or more symptoms 202, 204, 205 within symptom table 108 related to diagnosis 136. For example, if the user in the previous example provided diagnosis 136 indicating lower gastrointestinal tract cancer to user recommendation system 102 but did not identify symptom 134 for which recipe recommendations 122 are to be generated, user recommendation system 102 may identify constipation as an expected symptom 202, 204, 205 related to such diagnosis 136. Based on this expected symptom 202, 204, 205, user recommendation system 102 may generate dietary requirements 206, 208, 210 as described above.
[0040]
[0042] Next, the user recommendation system 102 may generate recipe requirements 216, 218, 220, 118 (block 306). As described above, the recipe requirements 216, 218, 220, 118 may identify food-based or other one or more restrictions for the recipes 164, 174 stored in the recipe database 162 and / or the recipe selection database 112 to comply with the previously generated meal requirements 114, 206, 208, 210. To generate the recipe requirements 216, 218, 220, 118, the user recommendation system 102 may consider the recipe requirement table 110 of the recommendation requirement database 104. For example, the user recommendation system 102 may identify one or more recipe requirements 216, 218, 220 in the recipe requirement table 110 that correspond to the previously generated meal requirements 206, 208, 210. Continuing with the previous example, the user recommendation system 102 may identify recipe requirements 216, 218, 220 that require a fiber level of 5 g or more per meal based on the meal requirements 206, 208, 210 that the user incorporates high-fiber foods.
[0041]
[0043] In some implementations, one or more of blocks 302, 304, and 306 may be optional. For example, if user recommendation system 102 has already received user information 132 from the user, method 300 may start at block 304 by identifying dietary requirements based on the previously received user information 132. Similarly, if user recommendation system 102 has stored dietary requirements 114, 206, 208, 210, and / or recipe requirements 216, 218, 220, 118 previously generated for a user, user recommendation system 102 may use the previously stored requirements at block 308 instead of regenerating the requirements at blocks 304, 306. However, in some implementations (e.g., when the user updates user information 132 when symptoms change), user recommendation system 102 may receive user information 132 corresponding to a user for whom user information 132 has been previously received. In such implementations, user recommendation system 102 may proceed to execute blocks 302, 304, 306 and update dietary requirements 114, 206, 208, 210 and / or recipe requirements 216, 218, 220, 118 based on the updated user information 132.
[0042]
[0044] Next, the user recommendation system 102 may generate a recipe recommendation 122 (block 308). The recipe recommendation 122 may be generated to include one or more recipes 124 that comply with the recipe requirements 216, 218, 220. Specifically, the user recommendation system 102 may identify one or more recipes 116, 120 in the recipe selection database 112 that have related recipe requirements 118 that are similar to or the same as the generated recipe requirements 216, 218, 220. The recipe recommendation 122 may additionally or alternatively be generated by identifying recipes 164, 174 in the recipe database 162 that comply with the recipe requirements 216, 218, 220. For example, such recipes 164, 174 may be identified based on one or more of the ingredient lists 166, 176, nutritional information 170, and / or tags 172, 180. In some implementations, the recipe generation system 142 may be configured to further generate recipes 124 for inclusion in the recipe recommendation 120 based on the identified recipes 164, 174 in the recipe database 160.
[0043]
[0045] In other implementations, the user recommendation system 102 may, instead of generating the recipe requirements 216, 218, 220 at block 306, identify a recipe 116 in the recipe selection database 112 that has meal requirements 114 that are similar to or the same as the meal requirements 206, 208, 210 identified at block 304.
[0044]
[0046] Recipe recommendation 122 may be presented to the user (e.g., via user device 130) when generated. To present to the user via a user interface, one or more recipes 124 may be included within recipe recommendation 120, and the user may use the user interface to view photos and other information regarding recipe 124 (e.g., extracted ingredient list 150 and / or generated nutritional information 154 and cooking instructions 156). In some implementations, if user device 130 and / or user information 132 has food preference information corresponding to the user, recipe 124 may be included in recipe recommendation 122 and / or the recipes 124 presented to the user via user device 130 may be filtered to take into account the provided food preference information (e.g., by excluding recipes that include ingredients identified as disliked by the user). In some implementations, the food preference information may be included in user information 132 and may be included as part of recipe requirements 216, 218, 220 identified at block 306. Additionally, recipe recommendation 122 may be generated as part of a meal plan generated for that user. For example, the meal plan may be generated to include recipes for the user's food consumption over a period of one week (e.g., breakfast, lunch, and dinner for 7 days) according to the user's dietary needs and / or preferences.
[0045]
[0047] Figure 4 shows a method 400 according to an exemplary embodiment of the present disclosure. The method 400 may be performed by the user recommendation system 102, the recipe generation system 142, and the recipe database 162 to add recipes 116, 120 to the recipe selection database 112. In certain implementations, the steps of method 400 may be performed prior to the execution of method 300. For example, method 400 may be executed to generate recipes 116, 120, and associated recipe requirements 118, and / or dietary requirements 114 of the recipe selection database 112 for later use in the execution of method 300. The method 400 may be implemented on a computer system such as system 100. For example, method 400 may be implemented by the user recommendation system 102, the user device 130, the recipe generation system 142, and / or the recipe database 162. The method 400 may also be implemented by a set of instructions stored on a computer-readable medium that, when executed by a processor, causes the computer system to execute the method. For example, all or part of method 400 may be implemented by CPUs 126, 138, 158 and memories 128, 140, 160. The following examples are described with reference to the flowchart shown in FIG. 4, but many other methods that perform operations related to FIG. 4 may be used. For example, the order of some of the blocks may be changed, some blocks may be combined with other blocks, one or more blocks may be repeated, and some of the described blocks may be optional.
[0046]
[0048] Method 400 begins with the recipe generation system 142 receiving an initial recipe from the recipe database 162 (block 402). The recipe generation system 142 may receive the initial recipe as a candidate base for a generated recipe to be included within the recipe selection database 112. In some implementations, the recipe generation system 142 may receive recipes from the recipe database 162 periodically (e.g., daily, weekly, monthly, quarterly). In other implementations, the recipe generation system 142 may receive the initial recipe when new recipes 164, 174 are added to the recipe database 162. In some implementations, the recipe generation system 142 may request an initial recipe from the recipe database 162 (e.g., by specifying one or more tags 171, 172, 179, 180 for which a recipe is desired). In some implementations, the recipe generation system 142 may receive the initial recipe via a network connection to the recipe database (e.g., an Internet connection or a local area network connection). In such implementations, the initial recipe may be received according to an application programming interface (API). The initial recipe may be implemented similarly to recipes 164, 174 and thus may include one or more of ingredient lists 166, 176, photos 168, 178, and nutritional information 170.
[0047]
[0049] Next, the recipe generation system 142 may extract an extracted ingredient list 150 and extracted tags 152 from the initial recipe (block 404). The recipe generation system 142 may copy this information from within the recipe itself (e.g., from ingredient lists 166, 176 and tags 171, 172, 179, 180 stored in association with the initial recipe in the recipe database 162). For example, if recipe 164 is the initial recipe, the extracted ingredient list 150 may include the same ingredients as ingredient list 166, and the extracted tags 152 may include one or both of tags 171, 172.
[0048]
[0050] Based on the extraction material list 150 and the extraction tag 152, the recipe generation system 142 may generate nutritional information 154 and cooking instructions 156 (block 406). In certain implementations, the nutritional information 154 and the cooking instructions 156 may be obtained from a recipe generation service. In other implementations, the recipe generation system 142 may generate the nutritional information 150 based on the materials included in the extraction material list 150 (e.g., based on the calories and other nutritional information of the constituent materials and the information on the amount of each material included in the extraction material list 150). The recipe generation system 142 may also generate the cooking instructions 156 based on previously processed recipes and / or one or more programmatic heuristics.
[0049]
[0051] Next, the recipe generation system 142 may combine the nutritional information 154 and the cooking instructions 156 with the extraction material list 150 and the extraction tag 152 to form a generated recipe (block 408). The generated recipe may include a data structure similar to the data structure of the recipe 164. For example, the extraction material list 150, the nutritional information 154, and the cooking instructions 156 may be stored within the generated recipe, and the extraction tag 152 may be stored in association with the generated recipe. In certain implementations, as described above, additional information such as a photo may be generated for inclusion within the generated recipe.
[0050]
[0052] Next, the generated recipe may be stored in the recipe selection database 112 (block 410). For example, after generating the generated recipe, the recipe generation system 142 may send the generated recipe to the user recommendation system 102 for storage in the recipe selection database 112. After being saved, the generated recipe may be utilized in subsequent recipe recommendation proposal 122 generation procedures. Specifically, the generated recipe may then be utilized in an analysis or other manner during the execution of method 300 (e.g., as recipes 116, 120 within the recipe selection database 112).
[0051]
[0053] The recipe selection database 112 may store the generated recipes in association with the extraction tags 152. For example, in one implementation, one or both of the recipe requirements 118 and the diet requirements 114 may correspond to the extraction tags 152 of the generated recipes. By storing the generated recipes in the recipe selection database 112 for future use, the user recommendation system 102 may be able to generate recipe recommendations 122 without relying on the recipe generation system 142 and / or the recipe database 162. Thus, in such an implementation, the complexity required to generate the recipe recommendations 122 may be reduced, thereby improving responsiveness and potentially shortening the time required to generate the recipe recommendations 122. In one implementation, the recipe selection database 112 may also store the recipes 116, 120 in association with tags (e.g., popularity or user ratings of the recipes 116, 120) that enable artificial intelligence-based improvements to the recipes 124 included in the recipe recommendations 122.
[0052]
[0054] In one implementation, at block 402, two or more initial recipes may be received by the recipe generation 142. In such an implementation, the recipe generation system 142 may repeatedly perform the processing at blocks 404, 406, and 408 to process each of the received initial recipes and generate a generated recipe corresponding to each of the received initial recipes. At block 410, the generated recipes may then be stored in the recipe selection database 112.
[0053]
[0055] In a further implementation, the method 400 may be performed before receiving the user information 132. For example, the method 400 may first be performed to enter the recipes 116, 120 into the recipe selection database 112 for each of the recipe requirements 216, 218, 220, or a subset thereof in the recipe requirements table 110 and / or for each of the diet requirements 206, 208, 210, or a subset thereof in the diet requirements table 106.
[0054]
[0056] In yet another implementation, blocks 406 and 408 may be optional. For example, instead, the recipe database 162 may communicate to the user recommendation system 102 a recipe 164, 174 that complies with the specified recipe requirements 216, 218, 220 in order to include it within the recipe recommendations 122. In such an implementation, the system 100 may not include the recipe generation system 142, and in additional or alternative implementations, the recipe selection database 112 may also be absent.
[0055]
[0057] All of the disclosed methods and procedures described in this disclosure can be implemented using one or more computer programs or components. These components may be provided as a series of computer instructions on any conventional computer-readable medium or machine-readable medium, including volatile and non-volatile memories such as RAM, ROM, flash memory, magnetic or optical disks, optical memory, or other storage media. The instructions may be provided as software or firmware and may also be implemented in whole or in part in hardware components such as ASICs, FPGAs, DSPs, or any other similar devices. The instructions may be configured to be executed by one or more processors that perform or facilitate the performance of all or part of the disclosed methods and procedures when executing a series of computer instructions.
[0056]
[0058] It should be understood that various changes and modifications to the embodiments described herein will be apparent to those skilled in the art. Such changes and variations can be made without departing from the spirit and scope of the subject matter of the present invention and without sacrificing the intended advantages. Therefore, such changes and variations are intended to be included within the scope of the appended claims.
[0057] This disclosure includes the following forms. [Claim 1] identifying user information indicative of symptoms affecting the user; identifying dietary requirements based on the symptoms; Identifying recipe requirements based on the dietary requirements; Presenting recipe recommendations to the user based on the recipe requirements; A method comprising the above. [Claim 2] The identifying of the user information includes: Receiving user information indicating the symptoms from the user; Identifying previously received user information indicating the symptoms; The method according to claim 1, comprising the above. [Claim 3] Identifying a plurality of recipes in a recipe selection database that comply with the recipe requirements; Selecting at least one selected recipe from among the plurality of recipes; Including the at least one selected recipe in the recipe recommendation; The method according to claim 1, further comprising the above. [Claim 4] The method according to claim 3, wherein the at least one selected recipe is selected from among the plurality of recipes according to user preferences related to the user information. [Claim 5] Receiving an initial recipe from a recipe database; Extracting a list of ingredients and related tags from the initial recipe; Generating nutritional information and cooking instructions based on the list of ingredients and the related tags; The method according to claim 1, further comprising the above. [Claim 6] Combining the nutritional information and the cooking instructions with the list of ingredients and the related tags to form a generated recipe; The method according to claim 5, further comprising the above. [Claim 7] Storing the generated recipe in a recipe selection database; The method according to claim 6, further comprising the above. [Claim 8] The method according to claim 1, wherein the dietary requirement specifies (i) a recipe or (ii) a type of food attribute related to alleviating or resolving the symptom. [Claim 9] The method according to claim 1, wherein the recipe requirement specifies one or more excluded materials, included materials, excluded material types, included material types, and / or nutritional requirements for conforming to the dietary requirement. [Claim 10] The method according to claim 1, wherein the symptom includes at least one condition selected from the group consisting of anorexia, xerostomia, weight loss, mucositis, nausea, dysphagia, constipation, and diarrhea. [Claim 11] A processor, A memory storing instructions, which, when executed by the processor, cause the processor to Implement a recommended requirement database including at least (i) a dietary requirement table storing a plurality of dietary requirements related to one or more symptoms and (ii) a recipe requirement table storing a plurality of recipe requirements related to the dietary requirements, And a user recommendation system, The user recommendation system Identifies user information indicating symptoms affecting the user, Identifies dietary requirements based on the symptoms in the dietary requirement table, Identifies recipe requirements based on the dietary requirements in the recipe requirement table, And presents recipe recommendations to the user based on the recipe requirements. System. [Claim 12] The user recommendation system Receives user information indicating the symptoms from the user, By identifying previously received user information indicating the symptoms, The system according to claim 11, configured to identify the user information. [Claim 13] When the memory stores further instructions and the further instructions are executed by the processor, the processor is caused to further implement a recipe selection database that stores a plurality of recipes related to the plurality of recipe requirements the user recommendation system identify a plurality of recipes that comply with the recipe requirements within the recipe selection database select at least one selected recipe from among the plurality of recipes The system according to claim 11, further configured such that the at least one selected recipe is included in the recipe recommendation proposal. [Claim 14] The system according to claim 13, wherein the at least one selected recipe is selected from among the plurality of recipes according to user preferences related to the user information. [Claim 15] When the memory stores further instructions and the further instructions are executed by the processor, the processor is caused to receive an initial recipe from a recipe database extract a list of ingredients and related tags from the initial recipe generate nutritional information and cooking instructions based on the list of ingredients and the related tags further implement a recipe generation system configured to The system according to claim 13. [Claim 16] the recipe generation system The system according to claim 15, further configured such that the nutritional information and the cooking instructions are combined with the list of ingredients and the related tags to form a generated recipe. [Claim 17] the recipe generation system The system according to claim 16, further configured such that the generated recipe is stored in the recipe selection database. [Claim 18] The system of claim 11, wherein the plurality of dietary requirements identify (i) a recipe or (ii) a type of food attribute related to alleviating or resolving the symptoms. [Claim 19] The system of claim 11, wherein the recipe requirements identify one or more excluded materials, included materials, excluded material types, included material types, and / or nutritional requirements for conforming to the dietary requirements. [Claim 20] Storing instructions that, when executed by a processor, cause the processor to Identify user information indicative of symptoms affecting the user, Identify dietary requirements based on the symptoms, Identify recipe requirements based on the dietary requirements, Present recipe recommendations to the user based on the recipe requirements. A non-transitory computer-readable medium.
Claims
1. identifying user information indicative of symptoms affecting a user undergoing treatment for a medical condition, the medical condition being cancer and the treatment being chemotherapy or radiation therapy; Identifying dietary requirements based on said symptoms; identifying recipe requirements based on said dietary requirements; presenting recipe recommendations to the user based on the recipe requirements; and Including, the dietary requirement identifies a type of (i) recipe or (ii) food attribute associated with alleviating or resolving the symptom; A method, wherein the recipe requirements specify one or more excluded ingredients, included ingredients, excluded ingredient types, included ingredient types, and / or nutritional requirements for complying with the dietary requirements.
2. Identifying the user information receiving user information from the user indicative of the symptom; identifying previously received user information indicative of the symptom; The method of claim 1 , comprising:
3. Identifying a plurality of recipes in a recipe selection database that comply with the recipe requirements; selecting at least one selected recipe from the plurality of recipes; including the at least one selected recipe in the recipe recommendations; The method of claim 1 further comprising:
4. The method of claim 3 , wherein the at least one selected recipe is selected from among the plurality of recipes according to user preferences associated with the user information.
5. receiving an initial recipe from a recipe database; extracting an ingredients list and associated tags from the initial recipe; generating nutritional information and cooking instructions based on the ingredient list and the associated tags; The method of claim 1 further comprising:
6. combining the nutritional information and the cooking instructions with the ingredients list and the associated tags to form a resulting recipe; The method of claim 5 further comprising:
7. storing the generated recipe in a recipe selection database; The method of claim 6 further comprising:
8. 2. The method of claim 1, wherein the symptoms include at least one condition selected from the group consisting of anorexia, xerostomia, weight loss, mucositis, nausea, dysphagia, constipation, and diarrhea.
9. The method of claim 1 , wherein the symptoms are caused by the treatment of the medical condition.
10. the medical condition is lower gastrointestinal tract cancer; the symptoms include constipation, identifying said dietary requirement based on said symptoms includes determining that said dietary requirement includes incorporating high fiber foods; The method of claim 1.
11. the symptoms include loss of appetite, Identifying the dietary requirement based on the symptoms includes determining whether the dietary requirement is: Incorporating high-protein foods Intake of high-calorie foods Eliminating low-fat foods; and Eliminate low-calorie foods, determining that the marker includes one or more of: The method of claim 1.
12. The symptoms include dysphagia, Identifying the dietary requirement based on the symptoms includes determining whether the dietary requirement is: Excluding coarse foods; and Eliminating hard foods, determining that the marker includes one or more of: The method of claim 1.
13. The method of claim 1 , wherein identifying the dietary requirements is further based on additional information including allergies of the user.
14. A processor; and a memory storing instructions that, when executed by the processor, cause the processor to: a recommendation requirement database including at least (i) a dietary requirement table storing a plurality of dietary requirements associated with one or more symptoms, and (ii) a recipe requirement table storing a plurality of recipe requirements associated with the dietary requirements; A user recommendation system is implemented, The user recommendation system comprises: identifying user information indicative of symptoms affecting a user undergoing treatment for a medical condition, wherein the medical condition is cancer and the treatment is chemotherapy or radiation therapy; Identifying said symptom-based dietary requirement in said dietary requirement table; identifying recipe requirements in the recipe requirements table based on the dietary requirements; presenting recipe recommendations to the user based on the recipe requirements; the plurality of dietary requirements identifies a type of (i) recipe or (ii) food attribute associated with alleviating or resolving the symptom; the recipe requirements identify one or more excluded ingredients, included ingredients, excluded ingredient types, included ingredient types, and / or nutritional requirements for complying with the dietary requirements; system.
15. The user recommendation system comprises: receiving user information from the user indicative of the symptom; By identifying previously received user information indicative of said symptom; The system of claim 14 configured to determine the user information.
16. The memory may store further instructions that, when executed by the processor, cause the processor to: further implementing a recipe selection database storing a plurality of recipes associated with the plurality of recipe requirements; The user recommendation system comprises: Identifying a plurality of recipes in the recipe selection database that comply with the recipe requirements; Selecting at least one selected recipe from the plurality of recipes; The system of claim 14 , further configured to include the at least one selected recipe in the recipe recommendations.
17. The system of claim 16 , wherein the at least one selected recipe is selected from among the plurality of recipes according to user preferences associated with the user information.
18. The memory may store further instructions that, when executed by the processor, cause the processor to: Receive the initial recipe from the recipe database, Extracting an ingredients list and associated tags from the initial recipe; Generate nutritional information and cooking instructions based on the ingredients list and the associated tags and further implementing a recipe generation system configured to:
17. The system of claim 16.
19. The recipe generation system comprises:
20. The system of claim 18, further configured to combine the nutritional information and the cooking instructions with the ingredients list and the associated tags to form a generated recipe.
20. The recipe generation system comprises: The system of claim 19 , further configured to store the production recipe in the recipe selection database.
21. The system of claim 14 , wherein the symptoms are caused by the treatment for the medical condition.
22. the medical condition is lower gastrointestinal tract cancer; the symptoms include constipation, identifying said dietary requirement based on said symptoms includes determining that said dietary requirement includes incorporating high fiber foods; The system of claim 14.
23. the symptoms include loss of appetite, Identifying the dietary requirement based on the symptoms includes determining whether the dietary requirement is: Incorporating high-protein foods Intake of high-calorie foods Eliminating low-fat foods; and Eliminate low-calorie foods, determining that the marker includes one or more of: The system of claim 14.
24. The symptoms include dysphagia, Identifying the dietary requirement based on the symptoms includes determining whether the dietary requirement is: Excluding coarse foods; and Eliminating hard foods, determining that the marker includes one or more of: The system of claim 14.
25. The system of claim 14 , wherein identifying the dietary requirements is further based on additional information including allergies of the user.
26. instructions that, when executed by a processor, cause the processor to: identifying user information indicative of symptoms affecting a user undergoing treatment for a medical condition, wherein the medical condition is cancer and the treatment is chemotherapy or radiation therapy; Identifying dietary requirements based on said symptoms; identifying recipe requirements based on said dietary requirements; providing recipe recommendations to the user based on the recipe requirements; the dietary requirement identifies a type of (i) recipe or (ii) food attribute associated with alleviating or resolving the symptom; the recipe requirements identify one or more excluded ingredients, included ingredients, excluded ingredient types, included ingredient types, and / or nutritional requirements for complying with the dietary requirements; Non-transitory computer-readable medium.