CN107705834A - A kind of dietary recommendations continued system based on Recognition with Recurrent Neural Network - Google Patents
A kind of dietary recommendations continued system based on Recognition with Recurrent Neural Network Download PDFInfo
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- CN107705834A CN107705834A CN201710933029.9A CN201710933029A CN107705834A CN 107705834 A CN107705834 A CN 107705834A CN 201710933029 A CN201710933029 A CN 201710933029A CN 107705834 A CN107705834 A CN 107705834A
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- 235000020979 dietary recommendations Nutrition 0.000 title claims abstract description 19
- 238000013528 artificial neural network Methods 0.000 title claims abstract description 18
- 230000000306 recurrent effect Effects 0.000 title claims abstract description 18
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- 230000037213 diet Effects 0.000 claims abstract description 47
- 230000036541 health Effects 0.000 claims abstract description 22
- 230000035764 nutrition Effects 0.000 claims description 9
- 235000016709 nutrition Nutrition 0.000 claims description 9
- 238000012544 monitoring process Methods 0.000 claims description 8
- 230000015572 biosynthetic process Effects 0.000 claims description 6
- 235000006286 nutrient intake Nutrition 0.000 claims description 6
- 238000012856 packing Methods 0.000 claims description 3
- 230000008859 change Effects 0.000 abstract description 9
- 235000015097 nutrients Nutrition 0.000 abstract description 9
- 235000020980 bad eating habits Nutrition 0.000 abstract description 8
- 235000006694 eating habits Nutrition 0.000 abstract description 6
- 208000001953 Hypotension Diseases 0.000 abstract description 4
- 208000021822 hypotensive Diseases 0.000 abstract description 4
- 230000001077 hypotensive effect Effects 0.000 abstract description 4
- 230000004580 weight loss Effects 0.000 abstract description 4
- 235000013305 food Nutrition 0.000 description 10
- 238000000034 method Methods 0.000 description 6
- 230000000378 dietary effect Effects 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 5
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- 238000004891 communication Methods 0.000 description 2
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- 235000021152 breakfast Nutrition 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
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Abstract
The invention provides a kind of dietary recommendations continued system based on Recognition with Recurrent Neural Network, the wherein system includes：Obtain user basic information and be sent to Cloud Server；The recommending recipes menu generated according to the user basic information；Cloud Server is sent to after recording actual diet recipe of the user according to recommending recipes menu setecting；According to the diet appraisal report of actual diet recipe generation and it is sent to intelligent terminal.In embodiments of the present invention, by being that user recommends suitable recipe according to user basic information, user is guided to change bad eating habit by easy stages, the weight loss program of oneself can be performed with guidance and supervision user, hypotensive plan or other plans, make life and the diet more nutrient health of user, realize analysis to user's eating habit and to the recipe recommendation based on user's history diet record information；User is allowed to get information about whether oneself lacks certain nutrient, effective to help user to change bad eating habit and preferred diet, the management user's of science eats, lives, OK.
Description
Technical field
The present invention relates to modern communication technology, depth learning technology, intelligent medical technical field, more particularly to one kind to be based on
The dietary recommendations continued system of Recognition with Recurrent Neural Network.
Background technology
With today's society expanding economy, living standards of the people more and more higher.With the improvement of living standards, medical treatment is defended
The improvement of carded sliver part, people also increasingly pay close attention to the health of oneself and household, if it is desired to whether understand the health of oneself
Lack certain nutrient, and whether understand the eating habit of oneself healthy, then diet record just becomes extremely important.Generally
In the case of, most people can all select to seek suggestion by nutritionist, and nutritionist is according to multiple dietary survey table come repeatedly
Understand the most real situation of diet of user, constantly provide the dietary recommendation of different foundations, but need to remember in dietary survey table
All foods and beverage of user's feed in a period of time, including snacks are recorded, are so got off, this manual record method is very numb
It is tired, and during nutritionist builds dietary survey table, user often forgets what oneself was eaten within the past period
Food.
Continuous application and development based on modern communication technology and medicine equipment, diet is recorded to analyze user's body situation
And the APP applications of recommending recipes also gradually increase, the diet recording method that the APP of big logarithm is used mainly includes：Self-defined hand
The methods of dynamic typing, voice typing, barcode scanning typing, search menu typing.
But whether using which kind of typing mode, when being required for the user to go the edible name of the dish of record or food materials, dosage, intake
Between and the inferior information of eating, if user does not record in time, then the feelings forgotten or misremembered still occur after a period of time
Condition, record is caused to malfunction；Therefore for many people, the diet record for adhering to not malfunctioning for a long time is all very troublesome one
Part thing.Recipe recommendation does not consider availability, does not consider recent recipe.Current techniques are simply to user
Physical trait is analyzed, and recommends corresponding recipe for him.So may be a continuous more days edible cool property food
The user of thing continues to recommend the food such as balsam pear, then recommendation now is exactly worthless.Last point is it not to user
Eating habit make certain analysis, some physical traits in user future are made prediction.
The content of the invention
It is an object of the invention to overcome the deficiencies in the prior art, the invention provides a kind of based on Recognition with Recurrent Neural Network
Dietary recommendations continued system, it can be that user recommends suitable recipe according to user basic information, user can be guided by easy stages
Change bad eating habit, the weight loss program of oneself, hypotensive plan or other plans can be performed with guidance and supervision user,
Make life and the diet more nutrient health of user, realize the analysis to user's eating habit and to remembering based on user's history diet
Record the recipe recommendation of information.User can be allowed to get information about whether oneself lacks certain nutrient, it is effective to help user to change
Become bad eating habit and preferred diet, the management user's of science eats, lives, OK.
In order to solve the above-mentioned technical problem, the invention provides a kind of dietary recommendations continued system based on Recognition with Recurrent Neural Network,
The system includes intelligent terminal and Cloud Server.
Preferably, the system also includes health monitoring equipment, and the health monitoring equipment is connected with intelligent terminal, for supervising
User health information is surveyed, and packing data information is sent to intelligent terminal.
Preferably, the intelligent terminal includes：
Acquisition module, for obtaining user basic information and being sent to Cloud Server；
First receiving module, the recommending recipes menu generated for receiving Cloud Server according to user basic information；
Logging modle, for recording user according to the actual diet recipe menu of recommending recipes menu setecting and being sent to cloud
Server；
Second receiving module, report is evaluated according to the diet of the actual diet recipe menu formation for receiving Cloud Server
Accuse.
Preferably, key addition button is additionally provided with the recommending recipes menu, for by special recommendation recipe menu
Upper all recipes are added to logging modle.
Preferably, the Cloud Server includes：
5th receiving module, the user basic information sended over for receiving acquisition module；
3rd generation module, for generating recommending recipes menu according to user basic information, it is sent to the first receiving module；
6th receiving module, the actual diet recipe menu sended over for receiving record module；
4th generation module, for according to actual diet recipe menu formation diet appraisal report, being sent to the second reception
Module.
Preferably, the 3rd generation module includes：
Determining unit, for determining user's body condition information according to user basic information；
First query unit, for inquiring about default recipe database, generate recommend corresponding with user's body condition information
Recipe menu.
Preferably, the Cloud Server is also connected including the second query unit with the 5th receiving module, default for inquiring about
Health database, generate reference nutrient intake level corresponding with user basic information.
Preferably, the 4th generation module includes：
Computing unit, for calculating the actual nutrition intake amount of user according to actual diet recipe；
Generation unit, for generating diet appraisal report according to actual nutrition intake amount and the reference nutrient intake level.
The invention provides a kind of dietary recommendations continued system based on Recognition with Recurrent Neural Network, by can according to user basic information
Think that user recommends suitable recipe, guide user to change bad eating habit by easy stages, can be used with guidance and supervision
Family performs the weight loss program of oneself, hypotensive plan or other plans, makes life and the diet more nutrient health of user, realizes
Analysis to user's eating habit and to the recipe recommendation based on user's history diet record information；User is allowed to get information about certainly
Whether oneself lacks certain nutrient, effective to help user to change bad eating habit and preferred diet, and the management of science is used
Eat, live, OK in family.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is the required accompanying drawing used in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, can be with
Other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 is a kind of structure composition signal of dietary recommendations continued system based on Recognition with Recurrent Neural Network in the embodiment of the present invention
Figure；
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, rather than whole embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art are obtained every other under the premise of creative work is not made
Embodiment, belong to the scope of protection of the invention.
Fig. 1 is a kind of structure composition signal of dietary recommendations continued system based on Recognition with Recurrent Neural Network in the embodiment of the present invention
Figure, as shown in figure 1, the system includes intelligent terminal and Cloud Server.
Specifically, the system also includes health monitoring equipment, and the health monitoring equipment is connected with intelligent terminal, for supervising
User health information is surveyed, and packing data information is sent to intelligent terminal.
Wherein, health monitoring equipment can be Intelligent weight scale, Intelligent bracelet, blood glucose meter, sphygmomanometer etc. by bluetooth,
The radio connections such as WiFi or ZigBee are connected with intelligent terminal.
Wherein, the intelligent terminal includes：
Acquisition module, for obtaining user basic information and being sent to Cloud Server；
Specifically, the user basic information includes userspersonal information and user health information；Userspersonal information is extremely
Include sex, age, height, body weight, nationality, residence, physical exertion intensity, history of disease, food prohibited, allergies, mouth less
One kind or any multiple combinations in taste preference；User health information is comprised at least one in body fat, blood pressure, blood fat, blood glucose, heart rate
Kind or any multiple combinations.
First receiving module, the recommending recipes menu generated for receiving Cloud Server according to user basic information；
Logging modle, for recording user according to the actual diet recipe menu of recommending recipes menu setecting and being sent to cloud
Server；
Second receiving module, report is evaluated according to the diet of the actual diet recipe menu formation for receiving Cloud Server
Accuse.
In a particular embodiment, key addition button is additionally provided with the recommending recipes menu, for by special recommendation
All recipes are added to logging modle on recipe menu.
Further, user carries out diet record according to recommending recipes menu in logging modle, including：
First way, when user carries out diet according to whole recipes on recommending recipes menu, then user only needs
" key the adds button " being arranged on recommending recipes menu is clicked on to send whole recipes in recommending recipes menu
Into logging modle.
The second way, when user has only eaten the course in recommending recipes menu, such as peeled shrimp pea carrot, then use
Family can click on the details page that the menu title in recommending recipes menu enters this menu, or user can be in recommending recipes dish
" peeled shrimp pea carrot " this course is retrieved in the search box set in list, the menu title is then clicked on and enters details page, detailed
" addition " shortcut is provided with below feelings page, then enters the logging modle page, meal, the use of food materials can be given tacit consent to from the background
Amount and edible date.User only needs to select modification can not change these information according to actual conditions, then clicks on " preservation " key.
The actual diet recipe of user's selection can be recorded and preserved by logging modle, and be sent to Cloud Server, by Cloud Server
It is further processed.
In a particular embodiment, the Cloud Server includes：
5th receiving module, the user basic information sended over for receiving acquisition module；
3rd generation module, for generating recommending recipes menu according to user basic information, it is sent to the first receiving module；
6th receiving module, the actual diet recipe menu sended over for receiving record module；
4th generation module, for according to actual diet recipe menu formation diet appraisal report, being sent to the second reception
Module.
Further, the 3rd generation module includes：
Determining unit, for determining user's body condition information according to user basic information；
First query unit, for inquiring about default recipe database, generate recommend corresponding with user's body condition information
Recipe menu.
Wherein, the Cloud Server is also connected including the second query unit with the 5th receiving module, default strong for inquiring about
Health database, generate reference nutrient intake level corresponding with user basic information.
Specifically, the recipe or the recipe of one day of a meal can be only included in the recommending recipes menu, is wrapped
Include：Breakfast, lunch, dinner and the recipe of each snack period, or one week even recipe of longer time section are planned.
Wherein, the recipe that regular meal can include a variety of menus and provide selection, and specific menu can be shown in recommending recipes menu
The information such as heat of the dosage of food materials and way and menu, can allow user clearly to understand each feed in title, menu
Intake.
Wherein, preset recipe database in, storage largely with various health corresponding points recipes, including fat-reducing
Crowd, pregnant and lying-in women, hyperpietic group, diabetic group and hyperlipemic patients group etc.；Also obtained in nutrition database
The mass data arrived, short-term or long-term recipe, various countries' dietary nutrition of urban residents element Dietary reference intakes including a large number of users with
And the recommending recipes suggestion given by nutritionist.
Wherein, second query unit is further comprised：
By being built to the vector of food species and main component, human body is conceived with the vector of physical trait；
Spliced and be trained as LSTM input node, obtain pushing away given by nutritionist in nutrition database
Recipe suggestion is recommended as penalty term, draws and represents vectorial compared with the storage recipe vector in advance recipe database, push away
Recommend similar recipe；
After obtaining the food materials species that should be included in recipe, meals gold word is combined according to the human body features obtained before
Tower generates specific intake.
Further, the 4th generation module includes：
Computing unit, for calculating the actual nutrition intake amount of user according to actual diet recipe；
Generation unit, for generating diet appraisal report according to actual nutrition intake amount and the reference nutrient intake level.
In embodiments of the present invention, by that can be that user recommends suitable recipe according to user basic information, in proper order gradually
Guide user to change bad eating habit with entering, the weight loss program of oneself, hypotensive meter can be performed with guidance and supervision user
Draw or other plans, make life and the diet more nutrient health of user, realize analysis to user's eating habit and to based on
The recipe recommendation of user's history diet record information；User is allowed to get information about whether oneself lacks certain nutrient, effectively
User is helped to change bad eating habit and preferred diet, the management user's of science eats, lives, OK.
One of ordinary skill in the art will appreciate that all or part of step in the various methods of above-described embodiment is can
To instruct the hardware of correlation to complete by program, the program can be stored in a computer-readable recording medium, storage
Medium can include：Read-only storage (ROM, Read Only Memory), random access memory (RAM, Random
Access Memory), disk or CD etc..
In addition, a kind of dietary recommendations continued system based on Recognition with Recurrent Neural Network provided above the embodiment of the present invention is carried out
It is discussed in detail, specific case used herein is set forth to the principle and embodiment of the present invention, above example
Explanation be only intended to help understand the present invention method and its core concept；Meanwhile for those of ordinary skill in the art,
According to the thought of the present invention, there will be changes in specific embodiments and applications, in summary, in this specification
Appearance should not be construed as limiting the invention.
Claims (8)
1. a kind of dietary recommendations continued system based on Recognition with Recurrent Neural Network, it is characterised in that the system includes intelligent terminal and cloud
Server.
2. the dietary recommendations continued system based on Recognition with Recurrent Neural Network as claimed in claim 1, it is characterised in that the system is also wrapped
Health monitoring equipment is included, the health monitoring equipment is connected with intelligent terminal, and for monitoring user health information, and packing data is believed
Breath is sent to intelligent terminal.
3. the dietary recommendations continued system based on Recognition with Recurrent Neural Network as claimed in claim 1, it is characterised in that the intelligent terminal
Including：
Acquisition module, for obtaining user basic information and being sent to Cloud Server；
First receiving module, the recommending recipes menu generated for receiving Cloud Server according to user basic information；
Logging modle, for recording user according to the actual diet recipe menu of recommending recipes menu setecting and being sent to cloud service
Device；
Second receiving module, for receiving diet appraisal report of the Cloud Server according to the actual diet recipe menu formation.
4. the dietary recommendations continued system based on Recognition with Recurrent Neural Network as claimed in claim 3, it is characterised in that the recommending recipes
Key addition button is additionally provided with menu, for all recipes on special recommendation recipe menu to be added into logging modle.
5. the dietary recommendations continued system based on Recognition with Recurrent Neural Network as claimed in claim 1, it is characterised in that the Cloud Server
Including：
5th receiving module, the user basic information sended over for receiving acquisition module；
3rd generation module, for generating recommending recipes menu according to user basic information, it is sent to the first receiving module；
6th receiving module, the actual diet recipe menu sended over for receiving record module；
4th generation module, for according to actual diet recipe menu formation diet appraisal report, being sent to the second receiving module.
6. the dietary recommendations continued system based on Recognition with Recurrent Neural Network as claimed in claim 5, it is characterised in that the 3rd generation
Module includes：
Determining unit, for determining user's body condition information according to user basic information；
First query unit, for inquiring about default recipe database, generate recommending recipes corresponding with user's body condition information
Menu.
7. the dietary recommendations continued system based on Recognition with Recurrent Neural Network as claimed in claim 6, it is characterised in that the Cloud Server
Also it is connected including the second query unit with the 5th receiving module, for inquiring about default Health database, generation is believed substantially with user
Reference nutrient intake level corresponding to breath.
8. such as the dietary recommendations continued system based on Recognition with Recurrent Neural Network as claimed in claim 5, it is characterised in that the 4th life
Include into module：
Computing unit, for calculating the actual nutrition intake amount of user according to actual diet recipe；
Generation unit, for generating diet appraisal report according to actual nutrition intake amount and the reference nutrient intake level.
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| CN201710933029.9A CN107705834A (en) | 2017-10-10 | 2017-10-10 | A kind of dietary recommendations continued system based on Recognition with Recurrent Neural Network |
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Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108846001A (en) * | 2018-04-11 | 2018-11-20 | 丽睿客信息科技（北京）有限公司 | The method and apparatus that menu is recommended |
| CN108899073A (en) * | 2018-06-29 | 2018-11-27 | 重庆邮电大学 | A kind of intelligent health diet recommender system of combination mobile terminal |
| CN109285597A (en) * | 2018-10-08 | 2019-01-29 | 北京健康有益科技有限公司 | A kind of dietotherapy recipe recommendation method, apparatus and readable medium |
| CN109360628A (en) * | 2018-11-26 | 2019-02-19 | 广东智源信息技术有限公司 | A kind of health diet nutrition guide method and system based on artificial intelligence |
| CN110059173A (en) * | 2019-04-19 | 2019-07-26 | 辽宁工程技术大学 | A kind of intelligent kitchen question and answer assistant system of knowledge based map |
| CN110275737A (en) * | 2019-06-25 | 2019-09-24 | 秒针信息技术有限公司 | A kind of control method and device for Intelligent water cup |
| WO2019179154A1 (en) * | 2018-03-19 | 2019-09-26 | Midea Group Co., Ltd. | Method and system for providing action recommendations associated with kitchen appliances |
| CN110379490A (en) * | 2019-07-19 | 2019-10-25 | 秒针信息技术有限公司 | Acquisition methods and device, storage medium, the electronic device in target dining room |
| CN111435610A (en) * | 2019-01-14 | 2020-07-21 | 珠海格力电器股份有限公司 | Method and device for recommending food and cooking appliance |
| CN111627525A (en) * | 2020-06-04 | 2020-09-04 | 曹庆恒 | Management method, system and equipment for diet related rules |
| CN112420159A (en) * | 2019-08-20 | 2021-02-26 | 广东美的白色家电技术创新中心有限公司 | Energy demand calculation processing method and device |
| CN112712873A (en) * | 2020-12-30 | 2021-04-27 | 昆山巨星行动电子商务有限公司 | Intelligent light diet scheme recommendation method and device |
| CN112735562A (en) * | 2021-01-25 | 2021-04-30 | 珠海格力电器股份有限公司 | Diet recommendation method and device, electronic equipment and storage medium |
| CN113344666A (en) * | 2021-06-02 | 2021-09-03 | 易食便当香港有限公司 | Method, device and system for generating menu |
| CN113470784A (en) * | 2021-06-24 | 2021-10-01 | 仲恺农业工程学院 | Recipe recommendation method and recipe recommendation system |
| CN113539426A (en) * | 2020-04-22 | 2021-10-22 | 深圳市前海高新国际医疗管理有限公司 | Nutrition evaluation system and method based on neural network deep learning algorithm |
| CN116417114A (en) * | 2023-06-06 | 2023-07-11 | 平安云厨科技集团有限公司 | Student healthy diet management system based on full life cycle |
| CN117198466A (en) * | 2023-11-08 | 2023-12-08 | 北京四海汇智科技有限公司 | Diet management method and system for kidney disease patients |
| CN117575849A (en) * | 2024-01-17 | 2024-02-20 | 广东优信无限网络股份有限公司 | Method for processing group meal and arranging meal, computer equipment and storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106228022A (en) * | 2016-07-29 | 2016-12-14 | 宁波方太厨具有限公司 | A kind of family based on individual physiological state meals commending system |
| CN106250673A (en) * | 2016-07-20 | 2016-12-21 | 美的集团股份有限公司 | A kind of dietary recommendations continued and evaluation methodology, intelligent terminal, Cloud Server and system |
-
2017
- 2017-10-10 CN CN201710933029.9A patent/CN107705834A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106250673A (en) * | 2016-07-20 | 2016-12-21 | 美的集团股份有限公司 | A kind of dietary recommendations continued and evaluation methodology, intelligent terminal, Cloud Server and system |
| CN106228022A (en) * | 2016-07-29 | 2016-12-14 | 宁波方太厨具有限公司 | A kind of family based on individual physiological state meals commending system |
Non-Patent Citations (1)
| Title |
|---|
| 李越: "个性化健康饮食推荐服务研究", 《中国优秀硕士学位论文全文数据库工程科技I辑》 * |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2019179154A1 (en) * | 2018-03-19 | 2019-09-26 | Midea Group Co., Ltd. | Method and system for providing action recommendations associated with kitchen appliances |
| CN108846001A (en) * | 2018-04-11 | 2018-11-20 | 丽睿客信息科技（北京）有限公司 | The method and apparatus that menu is recommended |
| CN108899073A (en) * | 2018-06-29 | 2018-11-27 | 重庆邮电大学 | A kind of intelligent health diet recommender system of combination mobile terminal |
| CN109285597A (en) * | 2018-10-08 | 2019-01-29 | 北京健康有益科技有限公司 | A kind of dietotherapy recipe recommendation method, apparatus and readable medium |
| CN109360628A (en) * | 2018-11-26 | 2019-02-19 | 广东智源信息技术有限公司 | A kind of health diet nutrition guide method and system based on artificial intelligence |
| CN111435610A (en) * | 2019-01-14 | 2020-07-21 | 珠海格力电器股份有限公司 | Method and device for recommending food and cooking appliance |
| CN110059173A (en) * | 2019-04-19 | 2019-07-26 | 辽宁工程技术大学 | A kind of intelligent kitchen question and answer assistant system of knowledge based map |
| CN110275737A (en) * | 2019-06-25 | 2019-09-24 | 秒针信息技术有限公司 | A kind of control method and device for Intelligent water cup |
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| CN112420159A (en) * | 2019-08-20 | 2021-02-26 | 广东美的白色家电技术创新中心有限公司 | Energy demand calculation processing method and device |
| CN113539426A (en) * | 2020-04-22 | 2021-10-22 | 深圳市前海高新国际医疗管理有限公司 | Nutrition evaluation system and method based on neural network deep learning algorithm |
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