講者: 林嶔博士 國防醫學大學醫學系教授
時間: 2026/3/11 (三) 12:10-14:00
地點: 管理大樓11樓-AI講堂 或 線上直播https://reurl.cc/GG72GG
報名連結: https://reurl.cc/R9AMeD或掃描海報QRcode
(教職員可獲得2小時活動時數認證，請上活動報名系統報名參加)
林嶔博士為資料科學家，專注建立具臨床實證基礎之醫療AI系統，整合電子病歷、心電圖與醫學影像資料，推動可改善病人結果的智慧決策工具。主持多項AI隨機對照試驗，成果發表於國際頂尖期刊。其AI-ECG系統獲TFDA核可與USFDA突破性醫材認定，並已部署於醫院與社區篩檢。本演講提出「Clinical AI Cycle」架構，說明臨床AI如何從訊號發現、務實型臨床試驗驗證，到真實世界部署。透過ECG、CXR與電子病歷等多模態資料辨識疾病風險，並結合預設臨床行動與隨機對照設計，使AI成為促發介入、改善預後的決策引擎，推動醫療由醫院延伸至社區與居家場域。
公告單位：智慧運算學院
承辦人：劉宇婷
聯絡分機：409-2501
Topic: The development of clinical AI cycle: from signal discovery to pragmatic trials and real-world deployment
Speaker: Professor Chin Lin, Department of Medicine, National Defense Medical University
Time: March 11, 2026 (Wednesday), 12:10 – 14:00 p.m.
Venue: The Management Building, 11F, AI Lecture Hall or Livestreaming https://reurl.cc/GG72GG
Registration: https://reurl.cc/R9AMeD or scan QR code on poster
Dr. Chin Lin is a data scientist specializing in clinical evidence standards for medical AI. His research integrates EHRs, ECG, and imaging data to develop actionable AI systems that improve patient outcomes. He has led multiple pragmatic randomized trials published in leading journals. His AI-ECG platform has received TFDA approval and USFDA Breakthrough Device Designation, and has been deployed in hospitals and community screening programs. This talk introduces the clinical AI cycle, a framework guiding AI from signal discovery to pragmatic trials and real-world deployment. Using ECGs, CXRs, and EHR data, multimodal models identify latent disease risks beyond traditional screening limits. AI is evaluated not only for prediction accuracy but for its ability to trigger clinical actions and improve outcomes. The framework enables scalable, evidence-based AI integration across hospitals, communities, and home healthcare settings.
Contact person：YUTING LIU
Contact number：409-2501