Intelligent nutrition and metabolism management system for tumor patients

Abstract

The invention discloses an intelligent nutrition and metabolism management system for tumor patients, and particularly relates to the technical field of intelligent management. Comprising a patient treatment duration division module, a patient treatment nutrition and metabolism information acquisition module, a patient treatment nutrition intelligent management module, a patient metabolism risk intelligent evaluation module, an auxiliary decision data analysis module, a patient treatment effect intelligent early warning module and a patient treatment nutrition and metabolism intelligent optimization module. According to the invention, the nutrition and metabolism monitoring data of each sub-period of the disease treatment duration of the target patient is collected, the nutrition state evaluation index and the metabolism function risk management index are calculated, and the patient treatment effect early warning index is obtained through analysis, so that the nutrition and metabolism conditions of the patient are intervened, the treatment effect evaluation accuracy is improved, and the patient treatment efficiency is improved. Waste of medical resources is reduced, and intelligent development of treatment effect decision making is promoted.

Description

Technical Field

[0001] The present invention relates to the field of intelligent management technology, and more specifically, to an intelligent system for nutrition and metabolism management of tumor patients. Background Art

[0002] In the intelligent management of nutrition and metabolism, the individual's genes, lifestyle, health history and metabolic characteristics are fully taken into consideration. By formulating a more personalized nutrition method and using data analysis technology to achieve the interconnection of medical and nutrition data, and providing intelligent analysis and evaluation, it is possible to regulate the differences in different individuals' responses to nutrition, improve the body's metabolic status and optimize individual health.

[0003] Cancer patients need more nutrition to ensure the growth of the tumor and the normal function of the body. Through information exchange, we help cancer patients and their families obtain dietary and nutritional knowledge, understand relevant policies, and develop reasonable eating habits and healthy lifestyle activities, so that patients can actively cooperate with the clinical implementation of nutritional metabolic treatment, and gradually form scientific and reasonable eating habits and improve nutritional status.

[0004] However, there are still some shortcomings in its actual use. For example, the existing methods for evaluating patient nutrition and metabolism often focus on physical indicators, which cannot fully reflect the nutritional and metabolic status of patients, and the risk identification of metabolic abnormalities is not comprehensive enough, resulting in the inability to carry out corresponding intervention measures. The nutritional and metabolic status of patients changes dynamically, but existing patient nutrition and metabolic management often lacks dynamic monitoring capabilities. For example, during the patient treatment process, timely detection and treatment of changes related to infusion and blood sugar are required to evaluate the impact on the metabolic status, thus leading to an imperfect early warning response mechanism for patient nutrition and metabolic management. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an intelligent system for nutrition and metabolism management of cancer patients, which is used to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solution: an intelligent system for nutrition and metabolism management of cancer patients, comprising: Patient treatment time division module: Based on the target patient's disease treatment time, the target patient's disease treatment time is divided into a sub-time period every i time periods, and each sub-time period of the target patient's disease treatment time is numbered.

[0007] Patient treatment nutrition and metabolic information collection module: used to collect the nutrition and metabolic monitoring data of each sub-period of the target patient's disease treatment duration. The patient treatment nutrition and metabolic information collection module includes a nutrition monitoring data collection unit, a metabolic monitoring data collection unit and an auxiliary decision-making data collection unit. The nutrition and metabolic monitoring data includes nutrition monitoring data, metabolic monitoring data and auxiliary decision-making data.

[0008] Patient treatment nutrition intelligent management module: used to calculate the nutritional status assessment index of each sub-period of the target patient's disease treatment duration based on the nutritional monitoring data of the nutritional monitoring data acquisition unit, and to warn the patient's treatment nutritional status.

[0009] Patient metabolic risk intelligent assessment module: used to calculate the metabolic function risk management index of each sub-period of the target patient's disease treatment duration based on the metabolic monitoring data of the metabolic monitoring data acquisition unit.

[0010] Auxiliary decision-making data analysis module: used to receive abnormal patient information transmitted by the patient treatment nutrition intelligent management module, and calculate the blood sugar variability and infusion safety index of each sub-period of the disease treatment time of abnormal patients according to the auxiliary decision-making data acquisition unit.

[0011] Intelligent early warning module for patient treatment effect: used to calculate the patient treatment effect early warning index for each sub-period of the disease treatment duration of abnormal patients based on the blood sugar variability, infusion safety index and metabolic function risk management index in each sub-period of the disease treatment duration of abnormal patients.

[0012] Patient treatment nutrition and metabolism intelligent optimization module: used to obtain the patient treatment effect warning index of each sub-period of the disease treatment time of abnormal patients, compare it with the preset patient treatment effect warning index, and process it.

[0013] Preferably, the patient treatment time division module is specifically: The target patient's disease treatment duration is divided into the initial period, and then the target patient's disease treatment duration is divided into a sub-period every i time periods, and the sub-periods of the target patient's disease treatment duration are numbered 1, 2,... ,... .

[0014] Preferably, the patient treatment nutrition and metabolic information collection module is specifically: Nutrition monitoring data collection unit: collects the energy intake, energy consumption, protein intake, and protein consumption of each sub-period of the target patient's disease treatment duration, and marks them as , , , ,in =1,2,... , Expressed as The number of the sub-period; Metabolic monitoring data collection unit: collects the water content, body fat percentage, and metabolic rate of each sub-period of the target patient's disease treatment duration, and marks them as , , ; Decision-making support data collection unit: collects the blood sugar variability and infusion safety index of each sub-period of the target patient's disease treatment duration, and marks them as , .

[0015] Preferably, the patient treatment nutrition intelligent management module is specifically: Step S01: The calculation formula of the nutritional status assessment index is:

[0016] in, Expressed as Nutritional status assessment index for each sub-period, Expressed as The number of the sub-period, Expressed as The duration of disease treatment in each sub-period, Expressed as The degree of energy consumption balance in each sub-period, Expressed as The degree of protein balance during each sub-period; Step S02: Obtain the nutritional status assessment index of each sub-period of the target patient's disease treatment duration, and compare it with the preset nutritional status assessment index. If the patient's nutritional status assessment index of a certain period is greater than the preset nutritional status assessment index, it indicates that the patient's nutritional management fluctuations in this period are too large, and patient treatment warning should be carried out. In this case, abnormal patient information is counted and transmitted to the patient treatment effect intelligent warning module. Otherwise, it indicates that the patient's nutritional management fluctuations in this period are normal. In this case, normal patient information is counted and transmitted to the patient metabolic risk intelligent assessment module.

[0017] Preferably, the patient treatment nutrition intelligent management module also includes: Step S01: Calculate the energy consumption balance degree according to the energy intake and energy consumption of each sub-period of the disease treatment duration of the target patient:

[0018] in, Expressed as The degree of energy consumption balance in each sub-period, Expressed as the preset energy consumption balance level, Expressed as Energy intake per sub-period, Expressed as The energy consumption per sub-period, Expressed as the permissible energy loss difference; Step S02: Calculate the protein balance level according to the protein intake and protein consumption of each sub-period of the target patient's disease treatment duration:

[0019] in, Expressed as The protein balance of each sub-period, Expressed as the preset protein balance level, Expressed as Protein consumption per sub-period, Expressed as Protein intake per sub-period, Expressed as the allowable difference in protein consumption, Expressed as a natural constant.

[0020] Preferably, the patient metabolic risk intelligent assessment module is specifically: Step S01: Obtain normal patient information and number the normal patients in sequence as 1, 2, ... ,... , the metabolic regulation index is calculated by the water content of each sub-period of the disease treatment time of normal patients:

[0021] in, Expressed as a metabolic regulation index, Expressed as Normal patient The moisture content of each sub-period, Expressed as The moisture content of each sub-period, It is represented as the number of normal patients, and n is represented as the number of sub-periods; Step S02: Calculate the metabolic rate control index based on the body fat percentage of each sub-period of the disease treatment duration of normal patients:

[0022] in, It is expressed as a metabolic rate control index. Expressed as Normal patient Body fat percentage in each period, Expressed as a preset body fat percentage; Step S03: The calculation formula of the metabolic function risk management index is:

[0023] in, Expressed as Metabolic function risk management index for each sub-period, Expressed as The metabolic rate of each sub-period, Expressed as Body fat percentage in each sub-period; Step S04: Obtain the metabolic function risk management index of each sub-period of the target patient's disease treatment duration, and compare it with the preset metabolic function risk management index. If the patient's metabolic function risk management index for a certain period of time is greater than the preset metabolic function risk management index, it indicates that the patient's metabolic function in this period is abnormal, and the abnormal patient information should be screened out for management; otherwise, it indicates that the patient's metabolic function in this period is normal.

[0024] Preferably, the auxiliary decision data analysis module is specifically: Step S01: Obtain abnormal patient information and number the abnormal patients in sequence as 1, 2, ... ,... , by collecting the values ​​and time of blood glucose monitoring in each sub-period of the disease treatment duration of abnormal patients, the blood glucose variability is calculated:

[0025] in, Expressed as Abnormal patient Blood sugar variability during each period, Expressed as Abnormal patient Sub-period The value of blood sugar monitoring, Expressed as Abnormal patient Sub-period The time of blood glucose monitoring, Expressed as the total number of blood glucose monitoring times, Expressed as The number of the blood glucose monitoring session; Step S02: Calculate the infusion safety index by collecting the temperature, speed, and concentration of the delivery solution in each sub-period of the disease treatment time of the abnormal patient:

[0026] in, Expressed as Abnormal patient Infusion safety indicators for each sub-period, Expressed as Abnormal patient Sub-period The temperature of the secondary delivery solution, Indicated as the preset delivery solution temperature, Expressed as Abnormal patient Sub-period The speed of delivering solution, Expressed as the preset delivery solution speed, Expressed as Abnormal patient Sub-period The concentration of the secondary delivery solution, Indicated as the preset delivery solution concentration.

[0027] Preferably, the calculation formula of the patient treatment effect warning index is:

[0028] in, Expressed as Abnormal patient Early warning index of treatment effect of patients in each sub-period, Expressed as The metabolic function risk management index of sub-periods is n, where n is the number of sub-periods. Expressed as Abnormal patient Blood sugar variability during each period, Expressed as Abnormal patient Infusion safety indicators for each sub-period.

[0029] Preferably, the patient treatment nutrition and metabolism intelligent optimization module is specifically: Obtain the patient treatment effect warning index of each sub-period of the disease treatment duration of abnormal patients, and calculate the difference with the preset patient treatment effect warning index. ,like If the difference is greater than the allowed value of the patient's treatment effect warning index, the patient's nutrition and metabolic status should be intervened to improve the treatment effect. Within the allowed difference, patients should be provided with early warning information of potential abnormalities in nutrition and metabolism.

[0030] Technical effects and advantages of the present invention: The present invention provides an intelligent system for nutrition and metabolism management of tumor patients. The system collects nutrition and metabolism monitoring data of each sub-period of the disease treatment time of the target patient, calculates the nutrition status assessment index of each sub-period of the disease treatment time of the target patient according to the nutrition monitoring data of the nutrition monitoring data acquisition unit, and compares it with the preset nutrition status assessment index. If the nutrition status assessment index of a certain period of the patient is greater than the preset nutrition status assessment index, it indicates that the fluctuation of the nutrition management of the patient in this period is too large, and the patient treatment warning should be carried out, then the abnormal patient information is counted, otherwise it indicates that the fluctuation of the nutrition management of the patient in this period is normal, then the normal patient information is counted, and the metabolic function risk management index of each sub-period of the disease treatment time of the target patient is calculated according to the metabolic monitoring data of the metabolic monitoring data acquisition unit, and compares it with the preset metabolic function risk management index. If the metabolic function risk management index of a certain period of the patient is greater than the preset metabolic function risk management index, then it indicates If there is an abnormality in the metabolic function of the patient during this period, the abnormal patient information should be screened out for management. Otherwise, it indicates that there is no abnormality in the metabolic function of the patient during this period. By real-time monitoring of the patient's nutrition and metabolic monitoring data, basic data support is provided for subsequent data analysis and nutrition evaluation. Through in-depth analysis of the nutrition monitoring data and metabolic monitoring data, it is helpful to more accurately understand the patient's nutrition and metabolic status, thereby enhancing the safety and effectiveness of patient treatment. The present invention provides an intelligent nutrition and metabolic management system for tumor patients. By collecting the values ​​and times of blood glucose monitoring in each sub-period of the disease treatment duration of abnormal patients, blood glucose variability is calculated. By collecting the temperature, speed and concentration of the delivery solution in each sub-period of the disease treatment duration of abnormal patients, an infusion safety index is calculated. Further, based on the metabolic function risk management index, a patient treatment effect warning index for each sub-period of the disease treatment duration of abnormal patients is calculated, and the difference between the patient treatment effect warning index and the preset patient treatment effect warning index is calculated. ,like If the difference is greater than the allowed value of the patient's treatment effect warning index, the patient's nutrition and metabolic status should be intervened to improve the treatment effect. Within the allowed difference, early warning information on potential abnormalities in nutrition and metabolism should be provided to patients. By monitoring the blood sugar levels and infusion parameters of the selected patients during the treatment stage, decision support for nutrition and metabolic early warning management is provided, which improves the accuracy of treatment effect evaluation, helps reduce the waste of medical resources, and thus promotes the intelligent development of treatment effect decision-making. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1It is a schematic diagram of the system module process connection of the present invention.

[0031] Figure 2 This is a schematic diagram of the structure of the patient treatment nutrition and metabolic information collection module of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments 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 creative work are within the scope of protection of the present invention.

[0033] See also Figure 1 As shown, the present invention provides an intelligent system for nutrition and metabolism management of tumor patients, including a patient treatment time division module, a patient treatment nutrition and metabolism information collection module, a patient treatment nutrition intelligent management module, a patient metabolic risk intelligent assessment module, an auxiliary decision data analysis module, a patient treatment effect intelligent early warning module, and a patient treatment nutrition and metabolism intelligent optimization module.

[0034] The patient treatment time division module is connected to the patient treatment nutrition and metabolism information collection module, the patient treatment nutrition and metabolism information collection module is connected to the patient treatment nutrition intelligent management module, the patient treatment nutrition intelligent management module is connected to the patient metabolic risk intelligent assessment module and the patient treatment effect intelligent early warning module, the patient metabolic risk intelligent assessment module is connected to the auxiliary decision-making data analysis module, the auxiliary decision-making data analysis module is connected to the patient treatment effect intelligent early warning module and the patient treatment nutrition and metabolism intelligent optimization module.

[0035] The patient treatment time division module divides the disease treatment time of the target patient into a sub-time period every i time periods based on the disease treatment time of the target patient, and numbers each sub-time period of the disease treatment time of the target patient.

[0036] In a possible design, the patient treatment time division module is specifically: The target patient's disease treatment duration is divided into the initial period, and then the target patient's disease treatment duration is divided into a sub-period every i time periods, and the sub-periods of the target patient's disease treatment duration are numbered 1, 2,... ,... .

[0037] See also Figure 2As shown, the patient treatment nutrition and metabolism information collection module is used to collect the nutrition and metabolism monitoring data of each sub-period of the target patient's disease treatment duration. The patient treatment nutrition and metabolism information collection module includes a nutrition monitoring data collection unit, a metabolism monitoring data collection unit and an auxiliary decision data collection unit. The nutrition and metabolism monitoring data includes nutrition monitoring data, metabolism monitoring data and auxiliary decision data.

[0038] In a possible design, the patient treatment nutrition and metabolic information collection module is specifically: Nutrition monitoring data collection unit: collects the energy intake, energy consumption, protein intake, and protein consumption of each sub-period of the target patient's disease treatment duration, and marks them as , , , ,in =1,2,... , Expressed as The number of the sub-period; Metabolic monitoring data collection unit: collects the water content, body fat percentage, and metabolic rate of each sub-period of the target patient's disease treatment duration, and marks them as , , ; Decision-making support data collection unit: collects the blood sugar variability and infusion safety index of each sub-period of the target patient's disease treatment duration, and marks them as , .

[0039] The patient treatment nutrition intelligent management module is used to calculate the nutrition status assessment index of each sub-period of the disease treatment duration of the target patient according to the nutrition monitoring data of the nutrition monitoring data acquisition unit, and to warn the patient of the treatment nutrition status.

[0040] In a possible design, the patient treatment nutrition intelligent management module is specifically: Step S01: Calculate the energy consumption balance degree according to the energy intake and energy consumption of each sub-period of the disease treatment duration of the target patient:

[0041] in, Expressed as The degree of energy consumption balance in each sub-period, Expressed as the preset energy consumption balance level, Expressed as Energy intake per sub-period, Expressed as The energy consumption per sub-period, Expressed as the permissible energy loss difference; Step S02: Calculate the protein balance level according to the protein intake and protein consumption of each sub-period of the target patient's disease treatment duration:

[0042] in, Expressed as The protein balance of each sub-period, Expressed as the preset protein balance level, Expressed as Protein consumption per sub-period, Expressed as Protein intake per sub-period, Expressed as the allowable difference in protein consumption, Expressed as a natural constant; Step S03: The calculation formula of the nutritional status assessment index is:

[0043] in, Expressed as Nutritional status assessment index for each sub-period, Expressed as The number of the sub-period, Expressed as The duration of disease treatment in each sub-period; Step S04: Obtain the nutritional status assessment index of each sub-period of the target patient's disease treatment duration, and compare it with the preset nutritional status assessment index. If the patient's nutritional status assessment index of a certain period is greater than the preset nutritional status assessment index, it indicates that the patient's nutritional management fluctuations in this period are too large, and a patient treatment warning should be issued. In this case, abnormal patient information is counted and transmitted to the patient treatment effect intelligent warning module. Otherwise, it indicates that the patient's nutritional management fluctuations in this period are normal. In this case, normal patient information is counted and transmitted to the patient metabolic risk intelligent assessment module.

[0044] The patient metabolic risk intelligent assessment module is used to calculate the metabolic function risk management index of each sub-period of the disease treatment duration of the target patient based on the metabolic monitoring data of the metabolic monitoring data acquisition unit.

[0045] In a possible design, the patient metabolic risk intelligent assessment module is specifically: Step S01: Obtain normal patient information and number the normal patients in sequence as 1, 2, ... ,... , the metabolic regulation index is calculated by the water content of each sub-period of the disease treatment time of normal patients:

[0046] in, Expressed as a metabolic regulation index, Expressed as Normal patient The moisture content of each sub-period, Expressed as The moisture content of each sub-period, It is represented as the number of normal patients, and n is represented as the number of sub-periods; Step S02: Calculate the metabolic rate control index based on the body fat percentage of each sub-period of the disease treatment duration of normal patients:

[0047] in, It is expressed as a metabolic rate control index. Expressed as Normal patient Body fat percentage in each period, Expressed as a preset body fat percentage; Step S03: The calculation formula of the metabolic function risk management index is:

[0048] in, Expressed as Metabolic function risk management index for each sub-period, Expressed as The metabolic rate of each sub-period, Expressed as Body fat percentage in each sub-period; Step S04: Obtain the metabolic function risk management index of each sub-period of the target patient's disease treatment duration, and compare it with the preset metabolic function risk management index. If the patient's metabolic function risk management index for a certain period of time is greater than the preset metabolic function risk management index, it indicates that the patient's metabolic function in this period is abnormal, and the abnormal patient information should be screened out for management; otherwise, it indicates that the patient's metabolic function in this period is normal.

[0049] The auxiliary decision data analysis module is used to receive abnormal patient information transmitted by the patient treatment nutrition intelligent management module, and calculate the blood sugar variability and infusion safety index of each sub-period of the disease treatment time of the abnormal patient according to the auxiliary decision data acquisition unit.

[0050] In a possible design, the auxiliary decision data analysis module is specifically: Step S01: Obtain abnormal patient information and number the abnormal patients in sequence as 1, 2, ... ,... , by collecting the values ​​and time of blood glucose monitoring in each sub-period of the disease treatment duration of abnormal patients, the blood glucose variability is calculated:

[0051] in, Expressed as Abnormal patient Blood sugar variability during each period, Expressed as Abnormal patient Sub-period The value of blood sugar monitoring, Expressed as Abnormal patient Sub-period The time of blood glucose monitoring, Expressed as the total number of blood glucose monitoring times, Expressed as The number of the blood glucose monitoring session; Step S02: Calculate the infusion safety index by collecting the temperature, speed, and concentration of the delivery solution in each sub-period of the disease treatment time of the abnormal patient:

[0052] in, Expressed as Abnormal patient Infusion safety indicators for each sub-period, Expressed as Abnormal patient Sub-period The temperature of the secondary delivery solution, Indicated as the preset delivery solution temperature, Expressed as Abnormal patient Sub-period The speed of delivering solution, Expressed as the preset delivery solution speed, Expressed as Abnormal patient Sub-period The concentration of the secondary delivery solution, Indicated as the preset delivery solution concentration.

[0053] The patient treatment effect intelligent early warning module is used to calculate the patient treatment effect early warning index for each sub-period of the disease treatment time of abnormal patients based on the blood sugar variability, infusion safety index, and metabolic function risk management index of each sub-period of the disease treatment time of abnormal patients.

[0054] In a possible design, the calculation formula of the patient treatment effect warning index is:

[0055] in, Expressed as Abnormal patient Early warning index of treatment effect of patients in each sub-period, Expressed as The metabolic function risk management index of sub-periods is n, where n is the number of sub-periods. Expressed as Abnormal patient Blood sugar variability during each period, Expressed as Abnormal patient Infusion safety indicators for each sub-period.

[0056] The patient treatment nutrition and metabolism intelligent optimization module is used to obtain the patient treatment effect warning index of each sub-period of the disease treatment time of abnormal patients, compare it with the preset patient treatment effect warning index, and process it.

[0057] In a possible design, the patient treatment nutrition and metabolism intelligent optimization module is specifically: Obtain the patient treatment effect warning index of each sub-period of the disease treatment duration of abnormal patients, and calculate the difference with the preset patient treatment effect warning index. ,like If the difference is greater than the allowed value of the patient's treatment effect warning index, the patient's nutrition and metabolic status should be intervened to improve the treatment effect. Within the allowed difference, patients should be provided with early warning information of potential abnormalities in nutrition and metabolism.

[0058] In the present embodiment, it should be specifically explained that the present invention collects the nutrition and metabolism monitoring data of each sub-period of the disease treatment duration of the target patient, calculates the nutrition status assessment index of each sub-period of the disease treatment duration of the target patient according to the nutrition monitoring data of the nutrition monitoring data acquisition unit, and compares the index with the preset nutrition status assessment index. If the nutrition status assessment index of a certain period of time of the patient is greater than the preset nutrition status assessment index, it indicates that the fluctuation of the nutrition management of the patient in this period is too large, and the patient treatment warning should be carried out, then the abnormal patient information is counted; otherwise, it indicates that the fluctuation of the nutrition management of the patient in this period is normal, then the normal patient information is counted, and according to the metabolic monitoring data of the metabolic monitoring data acquisition unit, the nutritional status assessment index of the target patient is calculated. The metabolic function risk management index of each sub-period of the target patient's disease treatment duration is calculated and compared with the preset metabolic function risk management index. If the patient's metabolic function risk management index of a certain period is greater than the preset metabolic function risk management index, it indicates that the patient's metabolic function in this period is abnormal, and the abnormal patient information should be screened out for management. Otherwise, it indicates that the patient's metabolic function in this period is normal. Real-time monitoring of the patient's nutrition and metabolic monitoring data provides basic data support for subsequent data analysis and nutritional evaluation. In-depth analysis of the nutrition monitoring data and metabolic monitoring data is conducive to a more accurate understanding of the patient's nutritional and metabolic status, thereby enhancing the safety and effectiveness of patient treatment.

[0059] The present invention calculates blood sugar variability by collecting the values ​​and time of blood sugar monitoring in each sub-period of the disease treatment time of abnormal patients, calculates the infusion safety index by collecting the temperature, speed and concentration of the delivery solution in each sub-period of the disease treatment time of abnormal patients, and further calculates the patient treatment effect warning index of each sub-period of the disease treatment time of abnormal patients based on the metabolic function risk management index, and performs difference calculation with the preset patient treatment effect warning index. ,like If the difference is greater than the allowed value of the patient's treatment effect warning index, the patient's nutrition and metabolic status should be intervened to improve the treatment effect. Within the allowed difference, early warning information on potential abnormalities in nutrition and metabolism should be provided to patients. By monitoring the blood sugar levels and infusion parameters of the selected patients during the treatment stage, decision support for nutrition and metabolic early warning management is provided, which improves the accuracy of treatment effect evaluation, helps reduce the waste of medical resources, and thus promotes the intelligent development of treatment effect decision-making.

[0060] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. Intelligent system for nutrition and metabolism management of cancer patients, characterized by: include: Patient treatment time division module: based on the target patient's disease treatment time, the target patient's disease treatment time is divided into a sub-period every i time periods, and each sub-period of the target patient's disease treatment time is numbered; Patient treatment nutrition and metabolism information collection module: used to collect nutrition and metabolism monitoring data of each sub-period of the disease treatment duration of the target patient, the patient treatment nutrition and metabolism information collection module includes a nutrition monitoring data collection unit, a metabolism monitoring data collection unit and an auxiliary decision data collection unit, and the nutrition and metabolism monitoring data includes nutrition monitoring data, metabolism monitoring data and auxiliary decision data; Intelligent management module for patient nutrition treatment: used to calculate the nutrition status evaluation index of each sub-period of the target patient's disease treatment duration based on the nutrition monitoring data of the nutrition monitoring data collection unit, and to warn the patient's nutrition status during treatment; Patient metabolic risk intelligent assessment module: used to calculate the metabolic function risk management index of each sub-period of the target patient's disease treatment duration based on the metabolic monitoring data of the metabolic monitoring data acquisition unit; Auxiliary decision data analysis module: used to receive abnormal patient information transmitted by the patient treatment nutrition intelligent management module, and calculate the blood sugar variability and infusion safety index of each sub-period of the disease treatment time of abnormal patients according to the auxiliary decision data acquisition unit; Intelligent early warning module for patient treatment effect: used to calculate the early warning index of patient treatment effect for each sub-period of the disease treatment duration of abnormal patients based on the blood sugar variability, infusion safety index, and metabolic function risk management index of each sub-period of the disease treatment duration of abnormal patients; Patient treatment nutrition and metabolism intelligent optimization module: used to obtain the patient treatment effect warning index of each sub-period of the disease treatment time of abnormal patients, compare it with the preset patient treatment effect warning index, and process it.

2. The intelligent system for nutrition and metabolism management of cancer patients according to claim 1, characterized in that: The patient treatment time division module is specifically as follows: The target patient's disease treatment duration is divided into the initial period, and then the target patient's disease treatment duration is divided into a sub-period every i time periods, and the sub-periods of the target patient's disease treatment duration are numbered 1, 2,... ,... .

3. The intelligent system for nutrition and metabolism management of cancer patients according to claim 1, characterized in that: The patient treatment nutrition and metabolic information collection module is specifically: Nutrition monitoring data collection unit: collects the energy intake, energy consumption, protein intake, and protein consumption of each sub-period of the target patient's disease treatment duration, and marks them as , , , ,in =1,2,... , Expressed as The number of the sub-period; Metabolic monitoring data collection unit: collects the water content, body fat percentage, and metabolic rate of each sub-period of the target patient's disease treatment duration, and marks them as , , ; Decision-making support data collection unit: collects the blood sugar variability and infusion safety index of each sub-period of the target patient's disease treatment duration, and marks them as , .

4. The intelligent system for nutrition and metabolism management of cancer patients according to claim 1, characterized in that: The patient treatment nutrition intelligent management module is specifically: Step S01: The calculation formula of the nutritional status assessment index is: in, Expressed as Nutritional status assessment index for each sub-period, Expressed as The number of the sub-period, Expressed as The duration of disease treatment in each sub-period, Expressed as The degree of energy consumption balance in each sub-period, Expressed as The degree of protein balance during each sub-period; Step S02: Obtain the nutritional status assessment index of each sub-period of the target patient's disease treatment duration, and compare it with the preset nutritional status assessment index. If the patient's nutritional status assessment index of a certain period is greater than the preset nutritional status assessment index, it indicates that the patient's nutritional management fluctuations in this period are too large, and patient treatment warning should be carried out. In this case, abnormal patient information is counted and transmitted to the patient treatment effect intelligent warning module. Otherwise, it indicates that the patient's nutritional management fluctuations in this period are normal. In this case, normal patient information is counted and transmitted to the patient metabolic risk intelligent assessment module.

5. The intelligent system for nutrition and metabolism management of cancer patients according to claim 4, characterized in that: The patient treatment nutrition intelligent management module also includes: Step S01: Calculate the energy consumption balance degree according to the energy intake and energy consumption of each sub-period of the disease treatment duration of the target patient: in, Expressed as The degree of energy consumption balance in each sub-period, Expressed as the preset energy consumption balance level, Expressed as Energy intake per sub-period, Expressed as The energy consumption per sub-period, Expressed as the permissible energy loss difference; Step S02: Calculate the protein balance level according to the protein intake and protein consumption of each sub-period of the target patient's disease treatment duration: in, Expressed as The protein balance of each sub-period, Expressed as the preset protein balance level, Expressed as Protein consumption per sub-period, Expressed as Protein intake per sub-period, Expressed as the allowable difference in protein consumption, Expressed as a natural constant.

6. The intelligent system for nutrition and metabolism management of cancer patients according to claim 1, characterized in that: The patient metabolic risk intelligent assessment module is specifically: Step S01: Obtain normal patient information and number the normal patients in sequence as 1, 2, ... ,... , the metabolic regulation index is calculated by the water content of each sub-period of the disease treatment time of normal patients: in, Expressed as a metabolic regulation index, Expressed as Normal patient The moisture content of each sub-period, Expressed as The moisture content of each sub-period, It is represented as the number of normal patients, and n is represented as the number of sub-periods; Step S02: Calculate the metabolic rate control index based on the body fat percentage of each sub-period of the disease treatment duration of normal patients: in, It is expressed as a metabolic rate control index. Expressed as Normal patient Body fat percentage in each period, Expressed as a preset body fat percentage; Step S03: The calculation formula of the metabolic function risk management index is: in, Expressed as Metabolic function risk management index for each sub-period, Expressed as The metabolic rate of each sub-period, Expressed as Body fat percentage in each sub-period; Step S04: Obtain the metabolic function risk management index of each sub-period of the target patient's disease treatment duration, and compare it with the preset metabolic function risk management index. If the patient's metabolic function risk management index for a certain period of time is greater than the preset metabolic function risk management index, it indicates that the patient's metabolic function in this period is abnormal, and the abnormal patient information should be screened out for management; otherwise, it indicates that the patient's metabolic function in this period is normal.

7. The intelligent system for nutrition and metabolism management of cancer patients according to claim 1, characterized in that: The auxiliary decision data analysis module is specifically: Step S01: Obtain abnormal patient information and number the abnormal patients in sequence as 1, 2, ... ,... , by collecting the values ​​and time of blood glucose monitoring in each sub-period of the disease treatment duration of abnormal patients, the blood glucose variability is calculated: in, Expressed as Abnormal patient Blood sugar variability during each period, Expressed as Abnormal patient Sub-period The value of blood sugar monitoring, Expressed as Abnormal patient Sub-period The time of blood glucose monitoring, Expressed as the total number of blood glucose monitoring times, Expressed as The number of the blood glucose monitoring session; Step S02: Calculate the infusion safety index by collecting the temperature, speed, and concentration of the delivery solution in each sub-period of the disease treatment time of the abnormal patient: in, Expressed as Abnormal patient Infusion safety indicators for each sub-period, Expressed as Abnormal patient Sub-period The temperature of the secondary delivery solution, Indicated as the preset delivery solution temperature, Expressed as Abnormal patient Sub-period The speed of delivering solution, Expressed as the preset delivery solution speed, Expressed as Abnormal patient Sub-period The concentration of the secondary delivery solution, Indicated as the preset delivery solution concentration.

8. The intelligent system for nutrition and metabolism management of cancer patients according to claim 1, characterized in that: The calculation formula of the patient treatment effect warning index is: in, Expressed as Abnormal patient Early warning index of treatment effect of patients in each sub-period, Expressed as The metabolic function risk management index of sub-periods is n, where n is the number of sub-periods. Expressed as Abnormal patient Blood sugar variability during each period, Expressed as Abnormal patient Infusion safety indicators for each sub-period.

9. The intelligent system for nutrition and metabolism management of cancer patients according to claim 1, characterized in that: The patient treatment nutrition and metabolism intelligent optimization module is specifically: Obtain the patient treatment effect warning index of each sub-period of the disease treatment duration of abnormal patients, and calculate the difference with the preset patient treatment effect warning index. ,like If the difference is greater than the allowed value of the patient's treatment effect warning index, the patient's nutrition and metabolic status should be intervened to improve the treatment effect. Within the allowed difference, patients should be provided with early warning information of potential abnormalities in nutrition and metabolism.

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