A Framework for T2D Management & Knowledge Discovery of Complications in the Context of Chinese Culture: From Triggers to Causalities

Mujiexin Liu, Jianqiang Xiao, Dazheng Zhang, Zhidong Jia

2022

Abstract

Background: With the ever-increasing number of Type-2 Diabetes (T2D) patients and its mortality rate in China, the medical care system is under huge pressure with all other related complications in the world’s largest population. Failing to afford the needed resources on T2D management after patients leaving the hospital, the burden and challenges of diabatic complications have become more acute than ever. In the context of the Chinese culture, especially the habits and priority of eating in the daily life makes it even harder for T2D patients to control and manage. Limited knowledge of complications and their causalities are the biggest challenges faced by doctors all around the world. Only with the knowledge on the progression and evolution of T2D and its complications can doctors have the opportunity to find solutions. To tackle this daunting challenge, a system is in urgent need that can collect the real-time, patient-generated data which will unveil the patterns about the triggers and causalities for better decision-making and, in the long run, provide an overarching understanding of the progression and evolution of T2D and its complications. Methods: To systematically place the data in the hands of patients, knowledge discovery based on data mining for the proposed framework can be of very high feasibility and accuracy. The triggers, anomalies in patients’ daily life, remind patients to provide the related data input for the analysis of the risk factors, patterns, and causalities of complications in the progression of T2D. Behind the triggers, the related known symptoms correlated with the internal organs, are classified by their severity and locations in bodies. Distant-aid like first responders will be arranged if very high-risk factors occur. Auto responses of suggestions will be given to patients if the condition is not urgent. The discovered patterns and causalities will be stored in the knowledge pool for future research and medicine development. Results : 1. The associations between and among the internal organs brought about by the patterns behind the triggers under urgent and non-urgent situations will give us answers to the current puzzles of the end-stage complications. 2. Supported by the updates of patient-provided data on the anomalies going on in their bodies, the data mining output of the correlation between internal organs and different complications can be of high accuracy with the "1 to 1", "1 to n" and "n to 1" relationships between symptoms and organs, organs and organs. 3. The collected symptoms correlating to the pathological changes of each individual internal organ can reshape our understanding about the functions of their own and as a part of the whole system of the human body. 4. The patterns of the known and newly discovered complications and their causalities will help doctors gain an overarching understanding of the progression and evolution of T2D and its complications. 5. The discovered knowledge will help doctors anticipate the upcoming progressions of diseases at an expert level with the level of comprehension well beyond the individual physician’s practice experience. Conclusions: With the application of this framework to the management of T2D and other chronic diseases for different groups of users, its knowledge pool will be continually enriched and enlarged. Its scalability on diseases and causalities will probably change many current definitions and enlarge the boundary of medical science.

Paper Citation

in Harvard Style

Liu M., Xiao J., Zhang D. and Jia Z. (2022). A Framework for T2D Management & Knowledge Discovery of Complications in the Context of Chinese Culture: From Triggers to Causalities. In Proceedings of the 1st International Conference on Health Big Data and Intelligent Healthcare - Volume 1: ICHIH, ISBN 978-989-758-596-8, pages 554-564. DOI: 10.5220/0011374200003438

in Bibtex Style

@conference{ichih22,
author={Mujiexin Liu and Jianqiang Xiao and Dazheng Zhang and Zhidong Jia},
title={A Framework for T2D Management & Knowledge Discovery of Complications in the Context of Chinese Culture: From Triggers to Causalities},
booktitle={Proceedings of the 1st International Conference on Health Big Data and Intelligent Healthcare - Volume 1: ICHIH,},
year={2022},
pages={554-564},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011374200003438},
isbn={978-989-758-596-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Health Big Data and Intelligent Healthcare - Volume 1: ICHIH,
TI - A Framework for T2D Management & Knowledge Discovery of Complications in the Context of Chinese Culture: From Triggers to Causalities
SN - 978-989-758-596-8
AU - Liu M.
AU - Xiao J.
AU - Zhang D.
AU - Jia Z.
PY - 2022
SP - 554
EP - 564
DO - 10.5220/0011374200003438