Taiwan’s aging population is growing at a faster rate, and 12.5 percent of the population is now 65 years or older. Due to the incidence of chronic diseases and degenerative illnesses in the aging population; it has increased the chances of polypharmacy. Each person in Taiwan visits the hospital on average 14 times annually and gets at least 4-5 medicines. Therefore, the total number of prescription per year is about 345 million. However, the rate of medication error is 0.5% to 5% which means that there are approximately 1.75 – 17.5 million inappropriate prescriptions in Taiwan. The clinical decision support system for prevention of medication error still needs much improvement. It is also claimed that 193 tons of medicine have been wasting annually because of poor medication compliance in Taiwan.
Artificial Intelligence (AI) has been entered the rapid development; it is expected that machine learning, deep learning, and natural language processing will become the major technology within 5 to 10 years. Owing to the availability of big data, artificial intelligence particularly machine learning is showing its potential in medicine area. As Taiwan has the world-class medical electronic data such as electronic medical records and health insurance database; therefore, it is a great opportunity of leveraging this database to develop AI in medicine.
This proposed project objective is, artificial intelligence for earlier and safer medicine in Taiwan as well as Worldwide. It includes (1) Create model and system for earlier and safer medicine, (2) Develop artificial empathy, (3) Randomized controlled trial, (4) Medical institutions used and reinforcement learning. It will exhibit Taiwan's strengths to promote the wisdom of the medical safety and improve patient medication compliance. It might connect Taiwan's industry, government, academia, research, medical, and international under one umbrella. In addition, it will contribute to precision medicine and talent education, and accelerate the link between artificial intelligence and industry, promote international cooperation and academic exchanges. Finally, it will help build to create "Earlier and Safer Medicine Worldwide" and this AI with Humanity, for Humanity.
In summary, this project will provide disease prediction, medicine optimization, medicine adherence and medical knowledge database such as disease-disease association, disease-medication association, medication- medication association. It will help to an improvement of medical treatments, ensure safety and quality care as well as advanced research and resource sharing.
PI Yu-Chuan Li
Professor, Graduate Institute of Biomedical Informatics, TMU
Co-PI Timothy Lane
Dean, College of Humanities and Social Sciences, TMU
Co-PI Bing-Fe Wu
Distinguished Professor, Department of Electrical and Control Engineering, NCTU
Co-PI Che-Ming Yang
Professor, School of Health Care Administration, TMU
Co-PI Shabbir Syed Abdul
Associate Professor, Graduate Institute of Biomedical Informatics, TMU
Co-PI Usman Iqbal
Assistant Professor, Master Program in Global Health and Development, College of Public Health, TMU