This book delves into the AI practical application in the association patterns & prediction models of diabetes complications. In view of dataset preprocessing and clustering, a fusion clustering algorithm is proposed in combination with the self-organizing map neural network, and the superiority of the improved algorithm is proved through comparative experiments, overcoming the sensitive clustering centers and uncertain number of clustering categories of the traditional fuzzy c-means algorithm. For designing the association pattern of diabetic complications based on the improved Apriori algorithm, matrix compression parallelization is investigated to improve the mining efficiency of the Apriori algorithm. At the same time, the PS interest degree is improved by combining subjective factors and rule credibility, and the IPSR interest degree measurement is proposed to ensure the effectiveness of the mining results. Then, a diabetes complication prediction model is established based on the improved least squares support vector machine. The sparrow search algorithm is used to optimize the model parameters, the prediction deviation is corrected in combination with the deep belief network to further improve the prediction accuracy, and the particle swarm optimization algorithm is used to realize the adaptive selection of the network structure. At last, an intelligent early warning system using the Vue.js framework and the Flask framework for diabetes complications is designed, which realizes the following functions such as visualization of common diabetes’ complication association patterns, prediction of diabetes complications, and query of diabetes patient information.

Shuli Guo is a full professor of Beijing Institute of Technology, the head of China geriatric disease standardized diagnosis and treatment society of CAGG, and a member of Chinese national technical committee for professional standardization. He was born in 1973 in Inner Mongolia, P.R. China. He received his bachelor’s degree (1995) and master’s degree (1998) from Inner Mongolia Normal University and his Ph.D. degree from Peking University (2001), and worked as a postdoctoral researcher from January 2002 to April 2004 at Tsinghua University, as a researcher fellow from January 2008 to September 2008 at Akita Prefectural University, and as a postdoctoral researcher from September 2008 to September 2009 at Oxford University. His research interests include medical image/data analysis, typical chronic disease analysis, and remote health monitoring. Recently, he has chaired 7 Chinese national standards and 5 Chinese industrial standards, more than 80 impactful papers, 7 monographs, 55 authorized Chinese patents, and 23 authorized software copyrights. He obtained the second prize for Beijing Municipal Government, the third prize for military medical achievements, the third prize of science and technology of the Chinese Medical Association, and the third prize of Beijing Medical Science and Technology. 

Lina Han is a research fellow in the Department of Cardiovascular Internal Medicine, the Second Medicine Center of Chinese PLA General Hospital, and Chinese PLA Medical School. She was born in 1973 in Jilin Province, P.R. China. She received her bachelor’s degree in medicine (1995), master’s degree in medicine (2000), and Ph.D. degree (2003) from Jilin University. She worked as a postdoctoral researcher from July 2003 to April 2005 at Chinese PLA General Hospital and as a research fellow from August 2008 to September 2009 at Kyoto University. Her research interests focus on many 3D modeling on cardiovascular systems, digital and intelligent management on chronic diseases and comorbidities in the elderly, and their medical solutions. Recently, she has published more than 100 impactful papers, 8 monographs, 50 authorized Chinese patents, 25 authorized software copyrights, and 7 Chinese national standards and 5 Chinese industrial standards. She obtained the first prize for Hainan Municipal Government, the second prize for Beijing Municipal Government, the first prize for military medical achievements, etc. 

Ms. Yanan Guo works as a software development engineer, and currently serves as a member of the China Geriatric Disease Standardized Diagnosis and Treatment Society of CAGG. She was born in 2000 in Shandong, P. R. China. She received her bachelor’s degree (2021) from Shandong University, and master’s degree (2024) from Beijing Institute of Technology. Her research field is the application of AI technology in health care, and the prediction of diabetes complications based on machine learning.