scholarly journals The Development of Integrated Medical Expert System for Diabetes Mellitus Patient

2020 ◽  
Vol 9 (2) ◽  
pp. 95-104
Author(s):  
Nina Sevani ◽  
Noviyanti Sagala ◽  
Evelline Kristiani
Keyword(s):  
Diabetes Mellitus ◽  
Treatment Guidelines ◽  
Healthy Lifestyle ◽  
Diabetes Mellitus Patient ◽  
Integrated System ◽  
Medical Expert ◽  
Inference Process ◽  
Medical Expert System ◽  
Causative Factors ◽  
The Stability

Diabetes Mellitus (DM) is a degenerative disease that has many causative factors. DM patients cannot recover completely but they can maintain the stability of their glucose level by following a healthy lifestyle. The goal of this research is to make an integrated system for people to promote a healthy lifestyle. This system also allows people to monitor the changes in their daily health conditions regularly. Main features in this system diagnose, treatment, guidelines for a healthy lifestyle, including a feature for counting and saving daily calorie consumption and physical activity. The system using the backward inference method to get the conclusion from a set of rules in the knowledge base. The verification using a query, validation with using recall and precision, and usability testing using a questionnaire, was conducted to test the performance of the system. The result of the testing shows that the system gives a good response to all queries given and the user also satisfied with the system. The recall value is 1 with the precision is 0.658. This precision value also promotes the inference process used in the system, which every user will suspect has DM when they start to use the diagnose feature.

An Integrated System for E-Medicine (E-Health, Telemedicine and Medical Expert Systems)

2010 ◽  
pp. 104-126
Author(s):  
Ivan Chorbev ◽  
Boban Joksimoski
Keyword(s):  
Medical Information ◽  
Medical Personnel ◽  
Rule Induction ◽  
Integrated System ◽  
Medical Expert ◽  
Web Based ◽  
Medical Expert System ◽  
Hybrid Heuristic Algorithm ◽  
Wireless Broadband ◽  
The Republic

This chapter presents an overview of an integrated system for eMedicine that the authors propose and implement in the Republic of Macedonia. The system contains advanced medical information systems, various telemedicine services supported by modern telecommunication technologies, and decision support modules. The authors describe their telemedicine services that use wireless broadband technologies (WiMAX, 3G, Wi-Fi). A significant part of the chapter presents a web based medical expert system that performs self training using a heuristic rule induction algorithm. The data inserted by medical personnel while using the e-medicine system is subsequently used for additional learning. The system is trained using a hybrid heuristic algorithm for induction of classification rules that we developed. The SA Tabu Miner algorithm (Simulated Annealing and Tabu Search based Data Miner) is inspired by both research on heuristic optimization algorithms and rule induction data mining concepts and principles.

An Integrated System for E-Medicine (E-Health, Telemedicine and Medical Expert Systems)

2011 ◽  
pp. 486-507
Author(s):  
Ivan Chorbev ◽  
Boban Joksimoski
Keyword(s):  
Medical Information ◽  
Medical Personnel ◽  
Rule Induction ◽  
Integrated System ◽  
Medical Expert ◽  
Web Based ◽  
Medical Expert System ◽  
Hybrid Heuristic Algorithm ◽  
Wireless Broadband ◽  
The Republic

This chapter presents an overview of an integrated system for eMedicine that the authors propose and implement in the Republic of Macedonia. The system contains advanced medical information systems, various telemedicine services supported by modern telecommunication technologies, and decision support modules. The authors describe their telemedicine services that use wireless broadband technologies (WiMAX, 3G, Wi-Fi). A significant part of the chapter presents a web based medical expert system that performs self training using a heuristic rule induction algorithm. The data inserted by medical personnel while using the e-medicine system is subsequently used for additional learning. The system is trained using a hybrid heuristic algorithm for induction of classification rules that we developed. The SA Tabu Miner algorithm (Simulated Annealing and Tabu Search based Data Miner) is inspired by both research on heuristic optimization algorithms and rule induction data mining concepts and principles.

Hypoglycemia in type 1 diabetes mellitus patient - factual ou factitious?

2014 ◽  
Author(s):  
Daniela Guelho ◽  
Isabel Paiva ◽  
Dircea Rodrigues ◽  
Carla Baptista ◽  
Joana Saraiva ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Type 1 Diabetes Mellitus ◽  
Diabetes Mellitus Patient

Modifikasi Resep Brownis Untuk Makanan Selingan Penderita Diabetes Mellitus

2017 ◽  
Vol 19 (2) ◽  
pp. 140
Author(s):  
Setyowati Setyowati
Keyword(s):  
Diabetes Mellitus ◽  
Nutritional Value ◽  
Food Selection ◽  
Diabetes Mellitus Patient ◽  
Fiber Content ◽  
Green Bean ◽  
Snack Food ◽  
Physical Quality ◽  
Organoleptic Quality ◽  
Red Bean

Background: The nutritional therapy management of diabetes mellitus patient lies in the proper diet and food selection arrangement. There is an eating recomendation (3 times for main food and 3 times of snackfood) that needed to be noted. One of the snack food that been allowed is brownie, as baked product and cake category. Modification on brownie recipe are needed to improve quality of the food. Objective: To understand a brownie recipe as snack food for diabetes mellitus patient based on physical quality, organoleptic quality, nutritional value and fiber content. Methods: The type of this research is an artificial experiment. The variables were modified brownie recipes; physical quality; organoleptic quality to colour, flavor, aroma, and texture; nutritional value, and fiber content. The subject of the study are 36 people with diabetes and 17 expert panelists. The object of this research is 3 kinds of brownie (red bean brownie, green bean brownie and peanut brownie). This research is conducted at Poltekkes Kemenkes Yogyakarta and Prolanis Organization in Puskemas Gamping 1 area, Sleman, Yogyakarta on February-September 2016. The data analysis of this research is done descriptively and analytically. Results: There is 3 brownie as modification results (green bean brownie, red bean brownie and peanut brownie). Those brownie have physical traits such as darker brown in colour, little bit sweet, have nutty flour aroma and little bit soft as a texture. Based on organoleptic quality, peanut brownie is the most preferred brownie. Based on analysis of chemical nutrition and fiber. Brownies tahat qualify the diet of people with diabetes mellitus is peanut brownie. Peanut brownie also been accepted by diabetes mellitus patient. Conclusion: Peanut brownie as modification results choosen as snack food alternatives for diabetes mellitus patient.

Role of Yoga in Lifestyle Disorders w.s.r. to Diabetes Mellitus Type-2

2019 ◽  
Vol 4 (03) ◽  
Author(s):  
Tushar K. Pardeshi ◽  
Sachinkumar Patil
Keyword(s):  
Diabetes Mellitus ◽  
Diabetes Mellitus Type 2 ◽  
Healthy Lifestyle ◽  
Working Hours ◽  
Behavioral Pattern ◽  
Current Trends ◽  
Diet Pattern ◽  
Speed And Accuracy

21st century is full of stress requiring more speed and accuracy. In today’s world of competition, diet pattern, lifestyle and behavioral pattern of people has changed. Late working hours, deadlines of work and stress have become a parcel of daily life. Due to this people have won’t have time for exercise and Yoga and end up in various lifestyle disorder, like Diabetes mellitus, Dyslipidemia, Obesity, Cardiovascular diseases etc. Diabetes mellitus is one of most leading disorder in all of them. The worldwide prevalence of D.M. has raised dramatically over past two decades, from an estimated 30 million cases in 1985 to 177 million in 2000. Based on current trends, > 360 million individuals will have diabetes by the year 2030. Diabetes mellitus is mentioned in our Samhitas as disorder of lethargic and exercise less lifestyle disorder and termed it as Madhumeha. Caused by mainly Apathyaahara and Viharsevana. Chikitsa of Madhumeha focused on Pathyaaahara and Vihar (lifestyle) in management of Madhumeha. This article is deal with healthy lifestyle including Yoga mentioned in Ayurveda Samhita for management of prevention and treatment of Lifestyle disorders.

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