There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | TING WEI WENG |
| Institution: | Taipei Medical University Hospital |
| Department: | TMUH Translational Imaging Research Center |
| Country: | |
| Proposed Analysis: | Building a national model of data hub for healthy aging - Background: Taiwan population is on the rapid slope of super-aging. The most concerned health issues caused by the aging society are happening not in the future but now. Among the elderly, brain and cardiovascular diseases have become the top causes of death, even surpassing the cancer. To face the challenge and to employ the opportunity of precision medicine, the key issues could be solved, if action could be taken early to prevent the aging population from sub-heath status o disease mode or disability, by developing high efficient screening AI landing products which are based on multi-dimension big data from high-risk sub-health patients. To achieve this goal, a new data-governing platform, using innovative artificial intelligence technologies to sieve out the novel risk biomarkers is up most important, not to mention the related ethical and regulatory issues on healthcare data. - Objectives: The overall goal of this single program project is to build a national model of data hub for healthy aging, thus landing AI products aiming at preventing brain and cardiovascular diseases in the aging population from sub health to disease mode can be achieved. Methods: This multi-center program project will focus on two most important diseases of the elderly, dementia and cardiovascular, as the research data governing substrate in order to build a state-of-the-art AI platform in healthcare system. We will integrate cross-sectional and longitudinal multi-dimensional patient data (including demography and lifestyle, clinical examinations, medical images, and genetic screening reports) from the four major medical centers (Taipei Medical University affiliated hospitals, National Taiwan University Hospital, Taipei Veterans General Hospital and National Cheng Kung University Hospital) across Taiwan. We will develop novel risk biomarkers for the neurodegenerative and cardiovascular diseases in the aging group. In addition, we will adopt multi-center big data and decentralized federated learning technology to construct a predictive map of health and aging, to tackle the bottleneck of artificial intelligence, to strengthen the trustworthiness, fairness and interpretability of AI models, and to develop A Fair AI system that can really be used in hospitals. Furthermore, this project will also use innovative data governance and shared data platform mechanisms to create a national model of data hub for healthy aging. - Importance: The ultimate benefit of this research project is to establish a health data hub model which can be adopted nationwide to develop a number of entrusted artificial intelligence products, to be used in hospitals and extended to communities in order to delay or avoid the high-risk population from progressing into dementia and cardiovascular disease, thus the healthcare resource can be managed, and the long-term care not to be overloading. We expect that the research results can help solve part of the problems of population aging imbalance in 2030, promote healthy aging, and reduce the financial burden of national health insurance. |
| Additional Investigators |
