Diet plan making system for evaluating perioperative period of patient based on AI

Abstract

The invention discloses a diet plan making system for evaluating patient perioperative period based on AI, and relates to the technical field of postoperative rehabilitation, and the key points of the technical scheme are that the system comprises the following modules: a patient information input module for inputting basic information of a patient; the physical condition evaluation module is used for evaluating physical conditions and symptoms of the patient; the energy demand calculation module is used for automatically identifying the energy demand of the patient; the diet plan matching module is used for matching personalized diet plans; the diet plan adjusting module is used for dynamically adjusting the diet plan according to the abdomen recovery condition of the patient; and the diet guidance output module is used for outputting detailed diet guidance. According to the technical scheme, through accurate data collection, dynamic diet plan adjustment, user-friendly interface design, data-driven decision support and real-time feedback and optimization, a scientific, personalized and easy-to-manage diet plan making system is provided for the patient after the abdominal operation.

Description

Technical Field

[0001] The present invention relates to the technical field of postoperative rehabilitation, and more particularly, to a system for formulating a diet plan for patients during perioperative period based on AI assessment. Background Art

[0002] In modern medicine, abdominal surgery is increasingly common, encompassing a wide range of procedures, from simple appendectomies to complex organ transplants. Advances in surgical techniques and improved anesthesia have significantly increased surgical success rates, leading to a corresponding rise in patient survival. However, postoperative recovery remains a complex and critical phase, directly impacting patients' quality of life and long-term health. Research has shown that postoperative dietary management is crucial for patient recovery. A balanced diet not only helps patients replenish essential nutrients but also promotes the recovery of intestinal function and reduces the risk of complications. Traditional dietary guidance often relies on physicians' experience and clinical knowledge, lacking systematicity and individualization, and may not meet the unique needs of each patient. Patients vary widely in their physical conditions, allergies, postoperative complications, and dietary preferences, making one-size-fits-all dietary plans often ineffective. Furthermore, with an aging population and an increasing number of patients with chronic diseases, healthcare systems are facing increasing pressure, making effective dietary management of postoperative patients a pressing issue.

[0003] Existing AI-based diet planning systems typically use machine learning and data mining technologies to provide patients with personalized diet recommendations by analyzing their basic information (such as age, gender, weight, height, etc.) and health status (such as allergy history, medical history, current symptoms, etc.), combined with nutritional principles and medical guidelines. These systems can automatically adjust diet plans based on the patient's specific situation, ensuring that the patient consumes adequate nutrition while avoiding foods that may cause discomfort. In addition, some systems can dynamically adjust diet plans based on the patient's recovery status to adapt to the patient's changing needs.

[0004] While existing AI-based diet planning systems have made progress in personalization and scientificity, several issues and challenges remain. First, data accuracy and completeness are key to system performance, but in reality, patient-provided data may be biased or incomplete, which can affect the accuracy of diet plans. Second, recovery conditions and dietary habits vary significantly among patients, requiring the system to flexibly address these differences and provide more diverse dietary recommendations. Summary of the Invention

[0005] The purpose of the present invention is to provide a diet plan formulation system based on AI assessment of patients during the perioperative period, so as to solve the problems of data accuracy and completeness and the inability to dynamically adjust the diet plan in the existing technology.

[0006] The above technical objectives of the present invention are achieved through the following technical solutions: a system for formulating a perioperative diet plan based on AI assessment of patients, the system comprising the following modules:

[0007] Patient information input module, used to input the patient's basic information, including but not limited to height, weight and allergy history;

[0008] Physical condition assessment module, used to assess the patient's physical condition and symptoms, including bowel sounds, abdominal pain, abdominal distension, nausea, vomiting, and flatulence and defecation;

[0009] Energy requirement calculation module, which is used to automatically identify the patient's energy requirements and calculate the required energy through nutritional measurement formulas;

[0010] A diet plan matching module is used to match personalized diet plans while excluding foods that patients are allergic to or cannot eat;

[0011] A diet plan adjustment module is used to dynamically adjust the diet plan according to the patient's abdominal recovery status;

[0012] The dietary guidance output module is used to output detailed dietary guidance, including the number of meals per day, the amount of food for each meal, and specific food types.

[0013] The present invention is further configured as follows: the system further includes:

[0014] a user interface that allows the user to input basic patient information and recovery data after abdominal surgery;

[0015] A database that stores nutritional measurement formulas, a food pyramid, food allergy information, and abdominal recovery assessment criteria;

[0016] An AI engine that analyzes input data and generates personalized diet plans;

[0017] Output module, used to display daily diet plan and specific portion of food.

[0018] The present invention is further configured as follows: the user interface includes a form and a symptom recording tool, the form is used to input the patient's height, weight, age and gender; the symptom recording tool is used to record the patient's bowel sounds, abdominal pain and bloating, nausea and vomiting, and flatulence and defecation.

[0019] The present invention is further configured as follows: the database includes a nutrition information database, a diet recommendation database and an allergy information database, which stores the nutritional components and calories of various foods; the diet recommendation database stores diet plans recommended according to different physical conditions; and the allergy information database stores the patient's allergy history and a list of foods that are not suitable for consumption.

[0020] The present invention is further configured such that the system can obtain the patient's basic information and abdominal condition through artificial intelligence dialogue.

[0021] The present invention is further configured such that the system can output specific recipes, including specific foods and serving sizes for breakfast, lunch, and dinner.

[0022] Another object of the present invention is to provide a method for using the above-mentioned AI-based evaluation-based post-abdominal surgery diet plan formulation system, the method comprising the following steps:

[0023] S1: Enter the patient's basic information and abdominal condition;

[0024] S2: Calculate the energy required by the patient;

[0025] S3: Provide personalized dietary recommendations;

[0026] S4: Eliminate foods that the patient is allergic to or should not eat;

[0027] S5: Adjust the diet plan according to the patient's recovery;

[0028] S6: Output a detailed diet plan.

[0029] By adopting the above technical solution, the present invention integrates a physical condition assessment module, an energy demand calculation module, a diet plan matching module, a diet plan adjustment module, and a diet guidance output module to meet the patient's personalized dietary needs. The system accurately collects the patient's basic information and recovery data after abdominal surgery, including height, weight, allergy history, and specific physical conditions and symptoms, through the patient information input module and the physical condition assessment module. The accuracy of these data is crucial for subsequent energy demand calculations and matching of personalized diet plans. The energy demand calculation module automatically identifies the patient's energy needs and calculates the required energy through a nutritional measurement formula, while the diet plan matching module excludes foods that the patient is allergic to or should not eat, ensuring the safety and personalization of the diet plan.

[0030] The system of the present invention is user-friendly and dynamically adjustable; the design of the user interface simplifies the data entry process, allowing patients and medical staff to easily input and update patient information. The integration of the AI ​​engine further enhances the intelligence level of the system, enabling it to obtain the patient's basic information and abdominal condition through artificial intelligence dialogue, reducing the need for manual input. The diet plan adjustment module allows the system to dynamically adjust the diet plan based on the patient's abdominal recovery to adapt to the patient's changing health status, ensuring that the diet plan is always in the best interests of the patient.

[0031] The present invention also provides an innovative method for using the above-mentioned system, including steps such as inputting patient information, calculating energy requirements, providing personalized dietary recommendations, eliminating allergic foods, adjusting the diet plan, and outputting a detailed diet plan. This methodological innovation not only improves the efficiency of diet planning but also provides a new solution for dietary management of patients after abdominal surgery. Through this method, the system can optimize diet plans in real time, ensuring that patients receive dietary recommendations that best suit their current health status, thereby promoting rapid recovery and improving their quality of life.

[0032] In summary, the present invention has the following beneficial effects:

[0033] 1. The system of the present invention uses integrated modules, such as the patient information input module and the physical condition assessment module, to accurately collect basic patient information and post-abdominal surgery recovery data. The accuracy of this data is crucial for subsequent energy requirement calculation and matching of personalized diet plans. The energy requirement calculation module automatically identifies the patient's energy needs and calculates the required energy using nutritional measurement formulas, while the diet plan matching module excludes foods to which the patient is allergic or inappropriate, ensuring the safety and personalization of the diet plan.

[0034] 2. The user interface design of the system of the present invention simplifies the data input process, allowing patients and medical staff to easily enter and update patient information. The integration of the AI ​​engine further enhances the intelligence level of the system, enabling it to obtain the patient's basic information and abdominal condition through artificial intelligence dialogue, reducing the need for manual input. The diet plan adjustment module allows the system to dynamically adjust the diet plan based on the patient's abdominal recovery status to adapt to the patient's changing health status, ensuring that the diet plan always serves the patient's best interests. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is an architectural diagram of a system for formulating a perioperative diet plan based on AI assessment of a patient in Example 1 of the present invention;

[0036] Figure 2 This is a flow chart of the method using Example 1 in Example 2 of the present invention. DETAILED DESCRIPTION

[0037] In order to enable those skilled in the art to better understand the present invention, the technical solution of the present invention will be further described in detail below in conjunction with the embodiments of the present invention and the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0038] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the embodiments.

[0039] Example 1: A system for formulating a perioperative diet plan based on AI assessment of patients, such as Figure 1 As shown, it includes a physical condition assessment module, an energy demand calculation module, a diet plan matching module, a diet plan adjustment module, and a diet guidance output module;

[0040] The patient information input module is designed as a touch screen interface with a drop-down menu and input box for entering the patient's basic information, such as height, weight, age, gender and allergy history. It also includes a "Submit" button for confirming that the information has been entered correctly and submitting the data.

[0041] The physical condition assessment module includes a symptom recording tool, which allows medical staff to record the patient's bowel sounds, abdominal pain, bloating, nausea, vomiting, and flatulence by checking a list or entering a description of the symptoms. It also provides a "real-time update" function that allows medical staff to update the patient's symptom changes at any time.

[0042] The energy requirement calculation module has built-in nutritional measurement formulas, such as the Mifflin-St Jeor equation, which is used to calculate the basal metabolic rate (BMR) based on the patient's gender, age, weight and height. The total energy requirement can be adjusted according to the patient's activity level and postoperative recovery stage.

[0043] The diet plan matching module selects a suitable diet plan from the diet suggestion library based on the patient's energy needs and physical condition, considers the patient's allergy information and foods that are not suitable for consumption, and automatically excludes these foods from the diet plan.

[0044] The diet plan adjustment module intelligently adjusts the diet plan based on the patient's daily recovery data and feedback, such as increasing protein intake to promote wound healing, and provides an "adjustment suggestion" interface to show why the diet plan needs to be adjusted and the expected effect.

[0045] The dietary guidance output module outputs detailed dietary guidance, including the number of meals per day, the amount of food for each meal, the specific types of food, as well as the cooking methods and nutritional information of the food. It provides a "print" function that allows medical staff to print the diet plan for patients to take home for reference.

[0046] The AI-based perioperative diet plan formulation system also includes an AI engine and a database. The AI ​​engine and database designs are shown below:

[0047] AI engine features:

[0048] Intelligent analysis: The AI ​​engine generates a personalized diet plan by analyzing the information and symptoms entered by the patient and combining it with the data in the database.

[0049] Self-learning: The AI ​​engine can continuously optimize the algorithm for generating diet plans based on patient feedback and recovery status.

[0050] Predictive model: The AI ​​engine can predict the patient's recovery trend and adjust the diet plan in advance to suit the patient's future needs.

[0051] Database Design:

[0052] The nutrition information database stores the nutritional composition and calories of various foods, including protein, fat, carbohydrates, vitamins and minerals.

[0053] The dietary recommendation library stores dietary plans recommended based on different physical conditions, such as low-fat diet, high-protein diet, low-fiber diet, etc.

[0054] The allergy information library stores the patient's allergy history and a list of foods that should not be eaten, as well as food ingredients that may cause allergic reactions.

[0055] The above database is designed to be an easily searchable structure so that the AI ​​engine can quickly access the required data, and the database is updated regularly to include the latest nutritional information and medical guidelines. The AI ​​engine first analyzes the patient's basic information, such as height, weight, and allergy history, to determine their basic nutritional needs. The AI ​​engine then selects a suitable diet plan from the diet recommendation library based on the patient's symptoms and recovery status. The AI ​​engine also takes into account the patient's personal dietary preferences to improve the acceptability of the diet plan. The AI ​​engine intelligently adjusts the diet plan based on the patient's daily feedback and recovery data. For example, if the patient has symptoms of indigestion, the AI ​​engine will reduce the fiber intake in the diet plan and increase the proportion of easily digestible foods.

[0056] The AI-based perioperative diet plan system also includes a user interface and a symptom recording tool. The user interface design and symptom recording tool functions are as follows:

[0057] User interface design: The user interface is designed as an intuitive and easy-to-use graphical interface with clear labels and prompts to guide users to complete information input. The interface provides multi-language support to accommodate patients and medical staff with different language backgrounds.

[0058] Symptom Recording Tool Features: The Symptom Recording Tool includes a symptom log where healthcare professionals can record daily symptom changes. The tool provides charts and graphs to visually demonstrate the patient's symptom trends.

[0059] The form of the present invention is designed as a step-by-step process, and each step contains necessary input fields and verification mechanisms to ensure the accuracy of the data. The form provides an automatic filling function, such as automatically calculating the BMI based on the patient's height and weight. The symptom recording tool of the present invention allows medical staff to record the patient's symptoms by checking a list or entering a description of the symptoms. The tool provides a "quick record" function, allowing medical staff to quickly select common symptoms to improve recording efficiency. The user interface is synchronized with the AI ​​engine and database in real time to ensure immediate updates and adjustments to the diet plan. The system of the present invention also provides a feedback mechanism that allows medical staff to make modification suggestions to the generated diet plan. These suggestions will be used by the AI ​​engine to optimize future diet plans.

[0060] Example 2: A method for using the above-mentioned AI-based evaluation-based post-abdominal surgery diet plan formulation system, comprising the following steps:

[0061] Information input: Medical staff enter the patient's basic information through the patient information input module, and the system automatically synchronizes the information to the database and AI engine.

[0062] Condition assessment: Medical staff use the physical condition assessment module to record the patient's specific symptoms. The system updates the patient's symptom changes in real time and notifies the AI ​​engine to adjust the diet plan.

[0063] Energy calculation: The energy demand calculation module automatically calculates the energy required by the patient based on the input data, and the results are displayed to medical staff through the user interface for review and adjustment.

[0064] Diet matching: The diet plan matching module generates a preliminary diet plan, taking into account the patient's allergy information and foods that should not be eaten. The preliminary diet plan is displayed to medical staff through the user interface for their review and modification.

[0065] Plan adjustment: Based on the patient's recovery progress, the diet plan adjustment module adjusts the diet plan. The adjustment suggestions are displayed to medical staff through the user interface for their confirmation or modification suggestions.

[0066] Guidance output: The dietary guidance output module provides a detailed diet plan, including specific foods and serving sizes for breakfast, lunch, and dinner. The system provides multiple output formats, including electronic and printed versions, to meet the needs of different patients.

[0067] This specific embodiment is merely an explanation of the present invention and is not intended to limit the present invention. After reading this specification, those skilled in the art may make non-creative modifications to this embodiment as needed. However, as long as such modifications are within the scope of the claims of the present invention, they are protected by patent law.

Claims

1. A diet planning system based on AI to evaluate patients during perioperative period, which is characterized by: The system includes the following modules: Patient information input module, used to input the patient's basic information, including but not limited to height, weight and allergy history; Physical condition assessment module, which is used to assess the patient's physical condition and symptoms, including bowel sounds, abdominal pain, bloating, nausea, vomiting, and flatulence and defecation; Energy requirement calculation module, which is used to automatically identify the patient's energy requirements and calculate the required energy through nutritional measurement formulas; A diet plan matching module is used to match personalized diet plans while excluding foods that patients are allergic to or cannot eat; A diet plan adjustment module is used to dynamically adjust the diet plan according to the patient's abdominal recovery status; The dietary guidance output module is used to output detailed dietary guidance, including the number of meals per day, the amount of food for each meal, and specific food types.

2. The system according to claim 1, characterized in that: The system further comprises: a user interface that allows the user to enter basic patient information and recovery data after abdominal surgery; A database that stores nutritional measurement formulas, food pyramids, food allergy information, and abdominal recovery assessment criteria; An AI engine that analyzes input data and generates a personalized diet plan; Output module, used to display daily diet plan and specific portion of food.

3. The system according to claim 2, characterized in that: The user interface includes a form and a symptom recording tool, wherein the form is used to input the patient's height, weight, age and gender; the symptom recording tool is used to record the patient's bowel sounds, abdominal pain and bloating, nausea and vomiting, and flatulence and defecation.

4. The system according to claim 2, characterized in that: The database includes a nutrition information database, a diet suggestion database and an allergy information database, which stores the nutritional components and calories of various foods; the diet suggestion database stores diet plans recommended according to different physical conditions; The allergy information database stores the patient's allergy history and a list of foods that are not suitable for consumption.

5. The system according to claim 1, characterized in that: The system can obtain the patient's basic information and abdominal condition through artificial intelligence dialogue.

6. The system according to claim 1, characterized in that: The system can output specific recipes, including specific foods and serving sizes for breakfast, lunch and dinner.

7. A method for using the AI-based evaluation-based abdominal postoperative diet plan formulation system according to any one of claims 1 to 6, characterized in that: The method comprises the following steps: S1: Enter the patient's basic information and abdominal condition; S2: Calculate the energy required by the patient; S3: Provide personalized dietary advice; S4: Eliminate foods that the patient is allergic to or cannot eat; S5: Adjust the diet plan according to the patient’s recovery; S6: Output a detailed diet plan.

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