Where Evidence‐Based Medicine Meets AI: Promise, Pitfalls, and Practice
Sangil Lee, Joshua Davis, Ken Milne, Christina Shenvi, Lars K Beattie, Martin Wegman, Laura Melville, Richard D Shih, Bryan Kane · 2026
Read Where Evidence‐Based Medicine Meets AI: Promise, Pitfalls, and Practice by Sangil Lee, Joshua Davis, Ken Milne, Christina Shenvi, Lars K Beattie, Martin Wegman, Laura Melville, Richard D Shih, Bryan Kane (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13284287.txt.
Description
Evidence-based medicine meets artificial intelligence in a 2026 practice paper by Sangil Lee and colleagues. Emergency care needs fast discovery, synthesis, and use of quality proof. The paper scopes AI help across retrieval, appraisal, synthesis, and application steps.
A short history opens the account, from John Shaw Billings onward. His catalog work grew into the Index Medicus and national library systems. Cholera literature demands in the 1870s showed why shared indexes matter. Modern AI promises faster evidence cycles for busy clinicians today. Pitfalls sit beside promise throughout the discussion sections. Practical guidance for emergency settings closes the paper.
Catalog record
| CREATOR | Sangil Lee, Joshua Davis, Ken Milne, Christina Shenvi, Lars K Beattie, Martin Wegman, Laura Melville, Richard D Shih, Bryan Kane |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 39158 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |