Non‐inferiority analysis of a fetal heart rate artificial intelligence algorithm to registered nurse assessment
Rohit Pardasani, Renee Vitullo, Sara Harris, Karen P Becker, Halit O Yapici, John W Beard · 2026
Read Non‐inferiority analysis of a fetal heart rate artificial intelligence algorithm to registered nurse assessment by Rohit Pardasani, Renee Vitullo, Sara Harris, Karen P Becker, Halit O Yapici, John W Beard (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/pmc-13520920.txt.
Description
Rohit Pardasani and co-authors test whether an AI reader of fetal heart traces matches nurse readers in work dated two thousand twenty-six. Heart and womb traces guide labor care, but human reads vary between and within readers. The algorithm blends deep learning with set rules to label the traces.
Trace data came from five United States hospitals, spanning two thousand thirteen to two thousand twenty-four. A panel of expert nurses accepted or rejected each read, from the AI and from staff nurses alike. Main checks covered the baseline rate, speed-ups, slow-downs, and contraction timing. The test asked whether the AI fell short of nurse reads by more than a set margin.
Catalog record
| CREATOR | Rohit Pardasani, Renee Vitullo, Sara Harris, Karen P Becker, Halit O Yapici, John W Beard |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 30 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |