Artificial Neural Networks Can Predict Early Failure of Cementless Total Hip Arthroplasty in Patients With Osteoporosis.
Christian KlemtIngwon YeoWayne Brian Cohen-LevyChristopher M MelnicYasamin HabibiYoung-Min KwonPublished in: The Journal of the American Academy of Orthopaedic Surgeons (2022)
The ML models presented in this study demonstrated high accuracy for the prediction of revision surgery in osteoporotic patients after primary noncemented THA. The presented ML models have the potential to be used by orthopaedic surgeons for preoperative patient counseling and optimization to improve the outcomes of primary noncemented THA in osteoporotic patients.
Keyphrases
- total hip arthroplasty
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- total knee arthroplasty
- bone mineral density
- prognostic factors
- peritoneal dialysis
- minimally invasive
- postmenopausal women
- neural network
- coronary artery disease
- case report
- total hip
- coronary artery bypass
- insulin resistance
- skeletal muscle
- surgical site infection