Can minimal clinically important differences in patient reported outcome measures be predicted by machine learning in patients with total knee or hip arthroplasty? A systematic review.
Benedikt LangenbergerAndreas ThomaVerena VogtPublished in: BMC Medical Informatics Decis. Mak. (2022)
Keyphrases
- systematic review
- computer assisted
- machine learning
- patient data
- clinical setting
- clinical data
- emergency department
- medical center
- clinical trials
- empirical studies
- healthy controls
- intraoperative
- patient groups
- medical treatment
- vital signs
- clinical information
- medical data
- intensive care
- therapy planning
- medical care
- medical doctors
- cognitive impairment
- primary care
- neurological disorders
- patient records
- blood pressure
- medical records
- medical experts
- clinically relevant
- intensive care unit
- medical staff
- liver disease
- medical knowledge
- clinical studies
- real patient data
- heart rate
- heart disease
- spinal cord injury
- breast cancer
- clinical practice
- intensive care units
- cancer patients
- breast cancer patients
- critical care
- disease progression
- prognostic factors
- medical practitioners
- acute coronary syndrome
- health related
- diabetic patients
- cardiovascular disease
- blood glucose
- medical practice
- diabetes mellitus
- tumor growth
- home care
- patient care
- hospital discharge
- health records
- operating room
- surgical procedures
- health care
- medical images