Artificial intelligence in total and unicompartmental knee arthroplasty
UG Longo, S De Salvatore, F Valente… - BMC Musculoskeletal …, 2024 - Springer
The application of Artificial intelligence (AI) and machine learning (ML) tools in total (TKA)
and unicompartmental knee arthroplasty (UKA) emerges with the potential to improve …
and unicompartmental knee arthroplasty (UKA) emerges with the potential to improve …
Concerns surrounding application of artificial intelligence in hip and knee arthroplasty: a review of literature and recommendations for meaningful adoption
Literature surrounding artificial intelligence (AI)-related applications for hip and knee
arthroplasty has proliferated. However, meaningful advances that fundamentally transform …
arthroplasty has proliferated. However, meaningful advances that fundamentally transform …
AutoPrognosis 2.0: Democratizing diagnostic and prognostic modeling in healthcare with automated machine learning
Diagnostic and prognostic models are increasingly important in medicine and inform many
clinical decisions. Recently, machine learning approaches have shown improvement over …
clinical decisions. Recently, machine learning approaches have shown improvement over …
Chat Generative Pretrained Transformer (ChatGPT) and Bard: artificial intelligence does not yet provide clinically supported answers for hip and knee osteoarthritis
JW Yang, KS Ardavanis, KE Slack, ND Fernando… - The Journal of …, 2024 - Elsevier
Background Advancements in artificial intelligence (AI) have led to the creation of large
language models (LLMs), such as Chat Generative Pretrained Transformer (ChatGPT) and …
language models (LLMs), such as Chat Generative Pretrained Transformer (ChatGPT) and …
Artificial intelligence and machine learning in prediction of surgical complications: current state, applications, and implications
Surgical complications pose significant challenges for surgeons, patients, and health care
systems as they may result in patient distress, suboptimal outcomes, and higher health care …
systems as they may result in patient distress, suboptimal outcomes, and higher health care …
An orthopaedic intelligence application successfully integrates data from a smartphone-based care management platform and a robotic knee system using a …
JH Lonner, MB Anderson, RE Redfern… - International …, 2023 - Springer
Purpose To evaluate the feasibility of using a smartphone-based care management platform
(sbCMP) and robotic-assisted total knee arthroplasty (raTKA) to collect data throughout the …
(sbCMP) and robotic-assisted total knee arthroplasty (raTKA) to collect data throughout the …
Construction of prediction model of deep vein thrombosis risk after total knee arthroplasty based on XGBoost algorithm
Y Chen, Y Jiang - Computational and Mathematical Methods in …, 2022 - Wiley Online Library
Objective. Based on the XGBoost algorithm, the prediction model of the risk of deep vein
thrombosis (DVT) in patients after total knee arthroplasty (TKA) was established, and the …
thrombosis (DVT) in patients after total knee arthroplasty (TKA) was established, and the …
Modern Applications of Machine Learning in Shoulder Arthroplasty: A Review
Modern Applications of Machine Learning in Shoulder Arthropl... : JBJS Reviews Modern
Applications of Machine Learning in Shoulder Arthroplasty: A Review : JBJS Reviews JBJS …
Applications of Machine Learning in Shoulder Arthroplasty: A Review : JBJS Reviews JBJS …
Comparative analysis of the ability of machine learning models in predicting in-hospital postoperative outcomes after total hip arthroplasty
MM El-Othmani, AK Zalikha… - JAAOS-Journal of the …, 2022 - journals.lww.com
Background: Machine learning (ML) methods have shown promise in a wide range of
applications including the development of patient-specific predictive models before surgical …
applications including the development of patient-specific predictive models before surgical …
Improved performance of machine learning models in predicting length of stay, discharge disposition, and inpatient mortality after total knee arthroplasty using patient …
Background This study aimed to compare the performance of ten predictive models using
different machine learning (ML) algorithms and compare the performance of models …
different machine learning (ML) algorithms and compare the performance of models …