Developing a machine learning algorithm to predict probability of retear and functional outcomes in patients undergoing rotator cuff repair surgery: protocol for a retrospective, multicentre study.
Laurens Jan Houterman AllaartSanne van SpanningLaurent LafosseThibault LafosseAlexandre LadermannGeorge S AthwalLaurent A M HendrickxJob N DoornbergMichel P J van den BekeromGeert Alexander Buijzenull nullPublished in: BMJ open (2023)
For safe multicentre data exchange and analysis, our Machine Learning Consortium adheres 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. Institutional Review Board approval does not apply to the current study protocol.
Keyphrases
- machine learning
- rotator cuff
- public health
- big data
- study protocol
- randomized controlled trial
- patients undergoing
- artificial intelligence
- electronic health record
- clinical trial
- minimally invasive
- deep learning
- healthcare
- mental health
- double blind
- health information
- open label
- surgical site infection
- data analysis
- atrial fibrillation
- drug administration
- neural network