Consensus Between Radiologists, Specialists in Internal Medicine, and AI Software on Chest X-Rays in a Hospital-at-Home Service: Prospective Observational Study
Abstract BackgroundHome hospitalization is a care modality growing in popularity worldwide. Telemedicine-driven hospital-at-home (HAH) services could replace traditional hospital departments for selected patients. Chest x-rays typically serve as a key diagnostic tool in such c...
Saved in:
| Main Authors: | Eitan Grossbard, Yehonatan Marziano, Adam Sharabi, Eliyahu Abutbul, Aya Berman, Reut Kassif-Lerner, Galia Barkai, Hila Hakim, Gad Segal |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2024-12-01
|
| Series: | JMIR Formative Research |
| Online Access: | https://formative.jmir.org/2024/1/e55916 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Deep generative abnormal lesion emphasization validated by nine radiologists and 1000 chest X-rays with lung nodules.
by: Shouhei Hanaoka, et al.
Published: (2024-01-01) -
Assessment of the effect of a comprehensive chest radiograph deep learning model on radiologist reports and patient outcomes: a real-world observational study
by: Andrew Johnson, et al.
Published: (2021-12-01) -
Impact of diffusion-weighted imaging on agreement between radiologists and non-radiologist in musculoskeletal tumor imaging using magnetic resonance
by: Gustav Lodeiro, et al.
Published: (2024-12-01) -
COVID-19 Deep Learning Prediction Model Using Publicly Available Radiologist-Adjudicated Chest X-Ray Images as Training Data: Preliminary Findings
by: Mohd Zulfaezal Che Azemin, et al.
Published: (2020-01-01) -
An educational beit midrash as a bridge between religious and secular identity
by: Galia Semo, et al.
Published: (2025-02-01)