Topic Extraction of Research Seeds by Natural Language Processing From Programs of Annual Scientific Meetings of the Japanese Circulation Society
Itaru Hosaka, Yukinori Akiyama, Marenao Tanaka, Tatsuya Sato, Masato Furuhashi · 2026
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Description
Itaru Hosaka and four colleagues show, in a 2026 study, how language software can mine a giant cardiology meeting program for research trends. Reading years of session listings by hand is slow and patchy. The team fed programs from the Japanese Circulation Society meetings of 2023 through 2026 into a Japanese language tool paired with topic modeling.
The software pulled 42,400 text blocks from the program files. Eight main research themes emerged from the wording. Coronary artery disease and heart failure held steady interest across the years. Team-based care involving many professions grew more visible. Fresh clusters formed around rhythm disorders and valve interventions. The authors present the workflow as a sturdy way for attendees and planners to spot rising topics without reading every page themselves.
Catalog record
| CREATOR | Itaru Hosaka, Yukinori Akiyama, Marenao Tanaka, Tatsuya Sato, Masato Furuhashi |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 6014 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |