Machine learning outcome prediction using stress perfusion cardiac magnetic resonance reports and natural language processing of electronic health records

Ebraham Alskaf; Simon M Frey; Cian M Scannell; Avan Suinesiaputra; Dijana Vilic; Vlad Dinu; Pier Giorgio Masci; Divaka Perera; Alistair Young; Amedeo Chiribiri

doi:10.1016/j.imu.2023.101418

Machine learning outcome prediction using stress perfusion cardiac magnetic resonance reports and natural language processing of electronic health records

Inform Med Unlocked. 2024:44:101418. doi: 10.1016/j.imu.2023.101418.

Authors

Affiliations

¹ School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom.
² Department of Cardiology, University Hospital Basel, Basel, Switzerland.
³ Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.
⁴ King's College London, United Kingdom.

No abstract available

Keywords: Cardiac magnetic resonance; Coronary artery disease; Electronic health records; Machine learning; Natural language processing; Outcome prediction.

Grants and funding

203148/WT_/Wellcome Trust/United Kingdom