A fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis
Beihang University · Wuhan University · +18 more institutions
Abstract
Coronavirus disease 2019 (COVID-19) has spread globally, and medical resources become insufficient in many regions. Fast diagnosis of COVID-19 and finding high-risk patients with worse prognosis for early prevention and medical resource optimisation is important. Here, we proposed a fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis by routinely used computed tomography.We retrospectively collected 5372 patients with computed tomography images from seven cities or provinces. Firstly, 4106 patients with computed tomography images were used to pre-train the deep learning system, making it learn lung features. Following this, 1266 patients (924 with COVID-19 (471 had follow-up…
Citation impact
- FWCI
- 51.56
- Percentile
- 100%
- References
- 34
Authors
16- SWShuo WangCorresponding
Beihang University
- YZYunfei Zha
Wuhan University, Renmin Hospital of Wuhan University
- WLWeimin Li
Sichuan University, West China Hospital of Sichuan University
- QWQingxia Wu
Northeastern University
- XLXiaohu Li
Anhui Medical University, First Affiliated Hospital of Anhui Medical University
Topics & keywords
- Medicine
- Deep learning
- Coronavirus disease 2019 (COVID-19)
- Pneumonia
- Artificial intelligence
- Computed tomography
- Disease
- Machine learning