[HTML][HTML] Predicting patient-reported outcomes following hip and knee replacement surgery using supervised machine learning
Background Machine-learning classifiers mostly offer good predictive performance and are
increasingly used to support shared decision-making in clinical practice. Focusing on …
increasingly used to support shared decision-making in clinical practice. Focusing on …
The utility of machine learning algorithms for the prediction of patient-reported outcome measures following primary hip and knee total joint arthroplasty
Background Patient-reported outcome measures (PROMs) are increasingly used as quality
benchmark in total hip and knee arthroplasty (THA; TKA) due to bundled payment systems …
benchmark in total hip and knee arthroplasty (THA; TKA) due to bundled payment systems …
[HTML][HTML] Can minimal clinically important differences in patient reported outcome measures be predicted by machine learning in patients with total knee or hip …
B Langenberger, A Thoma, V Vogt - BMC medical informatics and decision …, 2022 - Springer
Objectives To systematically review studies using machine learning (ML) algorithms to
predict whether patients undergoing total knee or total hip arthroplasty achieve an …
predict whether patients undergoing total knee or total hip arthroplasty achieve an …
[HTML][HTML] Predicting whether patients will achieve minimal clinically important differences following hip or knee arthroplasty: a performance comparison of machine …
B Langenberger, D Schrednitzki… - Bone & Joint …, 2023 - boneandjoint.org.uk
Aims A substantial fraction of patients undergoing knee arthroplasty (KA) or hip arthroplasty
(HA) do not achieve an improvement as high as the minimal clinically important difference …
(HA) do not achieve an improvement as high as the minimal clinically important difference …
Development of machine learning algorithms to predict patient dissatisfaction after primary total knee arthroplasty
KN Kunze, EM Polce, AJ Sadauskas… - The Journal of arthroplasty, 2020 - Elsevier
Background Postoperative dissatisfaction after primary total knee arthroplasty (TKA) that
requires additional care or readmission may impose a significant financial burden to …
requires additional care or readmission may impose a significant financial burden to …
Patient factors that matter in predicting hip arthroplasty outcomes: a machine-learning approach
J Sniderman, RB Stark, CE Schwartz, H Imam… - The Journal of …, 2021 - Elsevier
Background Despite the success of total hip arthroplasty (THA), approximately 10%-15% of
patients will be dissatisfied with their outcome. Identifying patients at risk of not achieving …
patients will be dissatisfied with their outcome. Identifying patients at risk of not achieving …
Can machine learning models predict failure of revision total hip arthroplasty?
C Klemt, WB Cohen-Levy, MG Robinson… - Archives of Orthopaedic …, 2023 - Springer
Introduction Revision total hip arthroplasty (THA) represents a technically demanding
surgical procedure which is associated with significant morbidity and mortality …
surgical procedure which is associated with significant morbidity and mortality …
Can machine learning algorithms predict which patients will achieve minimally clinically important differences from total joint arthroplasty?
MA Fontana, S Lyman, GK Sarker… - Clinical Orthopaedics …, 2019 - journals.lww.com
Background Identifying patients at risk of not achieving meaningful gains in long-term
postsurgical patient-reported outcome measures (PROMs) is important for improving patient …
postsurgical patient-reported outcome measures (PROMs) is important for improving patient …
Development of machine learning algorithms to predict clinically meaningful improvement for the patient-reported health state after total hip arthroplasty
KN Kunze, AV Karhade, AJ Sadauskas… - The Journal of …, 2020 - Elsevier
Background Failure to achieve clinically significant outcome (CSO) improvement after total
hip arthroplasty (THA) imposes a potential cost-to-risk imbalance in the context of bundle …
hip arthroplasty (THA) imposes a potential cost-to-risk imbalance in the context of bundle …
Development of machine learning algorithms to predict achievement of minimal clinically important difference for the KOOS‐PS following total knee arthroplasty
A Katakam, AV Karhade, A Collins… - Journal of …, 2022 - Wiley Online Library
As cost‐effective measures become increasingly implemented in the US healthcare system,
changes in patient‐reported outcome measure (PROM) scores can be utilized to indicate …
changes in patient‐reported outcome measure (PROM) scores can be utilized to indicate …