Name
Title | ||
|---|---|---|
AutoScribe: Extracting Clinically Pertinent Information from Patient-Clinician Dialogues. |
Abstract | ||
|---|---|---|
We present AutoScribe, a system for automatically extracting pertinent medical information from dialogues between clinicians and patients. AutoScribe parses the dialogue and extracts entities such as medications and symptoms, using context to predict which entities are relevant, and automatically generates a patient note and primary diagnosis. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3233/SHTI190510 | Studies in Health Technology and Informatics |
Keywords | Field | DocType |
Medical Records,Machine Learning,Medical Informatics | Medical physics,Medicine | Conference |
Volume | ISSN | Citations |
264 | 0926-9630 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Faiza Khan Khattak | 1 | 0 | 0.34 |
| Serena Jeblee | 2 | 5 | 1.82 |
| Noah H Crampton | 3 | 8 | 1.78 |
| Muhammad Mamdani | 4 | 11 | 2.74 |
| Frank Rudzicz | 5 | 231 | 44.82 |