Impact of automatic acquisition of key clinical information on the accuracy of electrocardiogram interpretation: a cross-sectional study
Shaohua Guo, Bufan Zhang, Yuanyuan Feng, Yajie Wang, Gary Tse, Tong Liu, Kang-Yin Chen · 2023
Read Impact of automatic acquisition of key clinical information on the accuracy of electrocardiogram interpretation: a cross-sectional study by Shaohua Guo, Bufan Zhang, Yuanyuan Feng, Yajie Wang, Gary Tse, Tong Liu, Kang-Yin Chen (2023) 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/pmc-10709941.txt.
Description
Shaohua Guo and six colleagues test whether automatically surfaced clinical details make doctors read heart tracings better, in a study published in two thousand twenty-three. ECG interpretation depends on context, but early in admission the chart is fragmentary. Their system mines records with language processing to serve key facts alongside the tracing.
Doctors of varying training read fifty ECGs on a plain system. After a two-week washout they reinterpreted the same tracings with the enriched system. Two cardiologists set the reference diagnoses independently. Accuracy differences measure the information's value. The study treats context as a diagnostic drug: dosed automatically, it may rescue readings that expertise alone cannot fix when the story is missing.
Catalog record
| CREATOR | Shaohua Guo, Bufan Zhang, Yuanyuan Feng, Yajie Wang, Gary Tse, Tong Liu, Kang-Yin Chen |
|---|---|
| YEAR | 2023 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 26 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |