Development and training of a machine learning algorithm to identify patients at risk for recurrence following an arthroscopic Bankart repair (CLEARER): protocol for a retrospective, multicentre, cohort study.
Sanne H van SpanningLukas P E VerweijLaurens J H AllaartLaurent A M HendrickxJob N DoornbergGeorge S AthwalThibault LafosseLaurent LafosseMichel P J van den BekeromGeert Alexander Buijzenull nullnull nullPublished in: BMJ open (2022)
For safe multicentre data exchange and analysis, our Machine Learning Consortium adhered to the WHO regulation 'Policy on Use and Sharing of Data Collected by WHO in Member States Outside the Context of Public Health Emergencies'. The study results will be disseminated through publication in a peer-reviewed journal. No Institutional Review Board is required for this study.
Keyphrases
- machine learning
- public health
- end stage renal disease
- big data
- clinical trial
- chronic kidney disease
- randomized controlled trial
- healthcare
- artificial intelligence
- deep learning
- electronic health record
- newly diagnosed
- peritoneal dialysis
- double blind
- health information
- global health
- patient reported
- anterior cruciate ligament reconstruction