AIMC Topic: Reoperation

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Application of machine learning in the context of reoperation, outcome and management after ACL reconstruction - A systematic review.

The Knee
INTRODUCTION: Machine learning-based tools are becoming increasingly popular in clinical practice. They offer new possibilities but are also limited in their reliability and accuracy.

AI classification of knee prostheses from plain radiographs and real-world applications.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
PURPOSE: Total knee arthroplasty (TKA) is considered the gold standard treatment for end-stage knee osteoarthritis. Common complications associated with TKA include implant loosening and periprosthetic fractures, which often require revision surgery ...

Indication model for laparoscopic repeat liver resection in the era of artificial intelligence: machine learning prediction of surgical indication.

HPB : the official journal of the International Hepato Pancreato Biliary Association
BACKGROUND: Laparoscopic repeat liver resection (LRLR) is still a challenging technique and requires a careful selection of indications. However, the current difficulty scoring system is not suitable for selecting indications. The purpose of this stu...

Clinical Application of Artificial Intelligence Preoperative Planning System Combined with Expert Database Retrieval in Complex Revision Hip Surgery.

Journal of visualized experiments : JoVE
Accurate preoperative planning in revision hip arthroplasty is crucial for achieving successful outcomes. To enhance the intuitive evaluation of acetabular bone defect severity and leverage previous successful experience in revision hip arthroplasty,...

Adverse Outcomes after Cemented and Cementless Primary Elective Total Hip Arthroplasty in 60,064 Matched Patients: A Study of Data from the Swedish Arthroplasty Register.

The Journal of arthroplasty
BACKGROUND: The choice between cemented and cementless fixation in primary elective total hip arthroplasty (THA) remains a subject of ongoing debate. However, comparisons between the two are subject to limited adjustments for patient characteristics,...

Machine learning models predicting risk of revision or secondary knee injury after anterior cruciate ligament reconstruction demonstrate variable discriminatory and accuracy performance: a systematic review.

BMC musculoskeletal disorders
BACKGROUND: To summarize the statistical performance of machine learning in predicting revision, secondary knee injury, or reoperations following anterior cruciate ligament reconstruction (ACLR), and to provide a general overview of the statistical p...

Predicting Early Hospital Discharge Following Revision Total Hip Arthroplasty: An Analysis of a Large National Database Using Machine Learning.

The Journal of arthroplasty
BACKGROUND: Revision total hip arthroplasty (rTHA) was recently removed from the Medicare inpatient-only list. However, appropriate candidate selection for outpatient rTHA remains paramount. The purpose of this study was to evaluate the utility of a ...

Predicting 30-day reoperation following primary total knee arthroplasty: machine learning model outperforms the ACS risk calculator.

Medical & biological engineering & computing
The ACS risk calculator (ARC) has proven less effective in predicting patient-specific risk of early reoperation after primary total knee arthroplasty (TKA), compromising care quality and cost efficiency. This study compared the performance of a mach...

Development and Validation of a Machine Learning-Based Nomogram for Prediction of Unplanned Reoperation Postspinal Surgery Within 30 Days.

World neurosurgery
BACKGROUND: Unplanned reoperation postspinal surgery (URPS) leads to prolonged hospital stays, higher costs, decreased patient satisfaction, and adversely affects postoperative rehabilitation. This study aimed to develop and validate prediction model...