TY - GEN
T1 - EHR-Based Mobile and Web Platform for Chronic Disease Risk Prediction Using Large Language Multimodal Models
AU - Liao, Chun Chieh
AU - Kuo, Wei Ting
AU - Hu, I. Hsuan
AU - Shih, Yen Chen
AU - Ding, Jun En
AU - Liu, Feng
AU - Hung, Fang Ming
N1 - Publisher Copyright:
© 2024 ACM.
PY - 2024/10/21
Y1 - 2024/10/21
N2 - Traditional diagnosis of chronic diseases involves in-person consultations with physicians to identify the disease. However, there is a lack of research focused on predicting and developing application systems using clinical notes and blood test values. We collected five years of Electronic Health Records (EHRs) from Taiwan's hospital database between 2017 and 2021 as an AI database. Furthermore, we developed an EHR-based chronic disease prediction platform utilizing Large Language Multimodal Models (LLMMs), successfully integrating with frontend web and mobile applications for prediction. This prediction platform can also connect to the hospital's backend database, providing physicians with real-time risk assessment diagnostics. The demonstration link can be found at https://www.youtube.com/watch?v=oqmL9DEDFgA
AB - Traditional diagnosis of chronic diseases involves in-person consultations with physicians to identify the disease. However, there is a lack of research focused on predicting and developing application systems using clinical notes and blood test values. We collected five years of Electronic Health Records (EHRs) from Taiwan's hospital database between 2017 and 2021 as an AI database. Furthermore, we developed an EHR-based chronic disease prediction platform utilizing Large Language Multimodal Models (LLMMs), successfully integrating with frontend web and mobile applications for prediction. This prediction platform can also connect to the hospital's backend database, providing physicians with real-time risk assessment diagnostics. The demonstration link can be found at https://www.youtube.com/watch?v=oqmL9DEDFgA
KW - chronic disease prediction system
KW - electronic health records
KW - large language models
UR - http://www.scopus.com/inward/record.url?scp=85210002329&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85210002329&partnerID=8YFLogxK
U2 - 10.1145/3627673.3679227
DO - 10.1145/3627673.3679227
M3 - Conference contribution
AN - SCOPUS:85210002329
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 5244
EP - 5248
BT - CIKM 2024 - Proceedings of the 33rd ACM International Conference on Information and Knowledge Management
T2 - 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024
Y2 - 21 October 2024 through 25 October 2024
ER -