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Understanding Patient and Physiotherapist Requirements for a Personalized Automated Smartphone Telemonitored App for Posttotal Knee Arthroplasty Rehabilitation: Qualitative Study

Understanding Patient and Physiotherapist Requirements for a Personalized Automated Smartphone Telemonitored App for Posttotal Knee Arthroplasty Rehabilitation: Qualitative Study

Recognizing the need for repeated reference, participants see the advantage of housing these materials in an app for convenient access: You want to give the patient information that he needs, you want to avoid giving him information that he doesn’t need and devalue the app. Some after surgery they call in to a physio, not every time the physios are available. But if you see from the app, you can always play it again and again until they understand.

Eleanor Shuxian Chew, Aileen Eugenia Scully, Samanth Shi-Man Koh, Ee-Lin Woon, Juanita Krysten Miao-Shi Low, Yu-Heng Kwan, John Wei-Ming Tan, Yong-Hao Pua, Celia Ia-Choo Tan, Luke Jonathan Haseler

JMIR Rehabil Assist Technol 2025;12:e59688

A Risk Prediction Model (CMC-AKIX) for Postoperative Acute Kidney Injury Using Machine Learning: Algorithm Development and Validation

A Risk Prediction Model (CMC-AKIX) for Postoperative Acute Kidney Injury Using Machine Learning: Algorithm Development and Validation

Nonbinary data were one-hot encoded, a method for rearranging categorical data into binary variables, and numerical data were normalized using min-max scaling. This would convert all numeric values between or equal to a value of 0 and 1. Min-max scaling is given by: One-hot encoding, min-max scaling, and dataset splitting were accomplished using the Scikit-Learn library (version 0.24.2) [24]. These steps are required to improve the performance of machine learning models and training stability.

Ji Won Min, Jae-Hong Min, Se-Hyun Chang, Byung Ha Chung, Eun Sil Koh, Young Soo Kim, Hyung Wook Kim, Tae Hyun Ban, Seok Joon Shin, In Young Choi, Hye Eun Yoon

J Med Internet Res 2025;27:e62853

Effect of Home-Based Virtual Reality Training on Upper Extremity Recovery in Patients With Stroke: Systematic Review

Effect of Home-Based Virtual Reality Training on Upper Extremity Recovery in Patients With Stroke: Systematic Review

Similarly, Allegue et al [32] found that moderate-intensity interventions (30 min, 5 times a wk) for 3 months led to significant improvements in FMA-UE and MAL, underscoring the value of structured, long-term interventions. Wilson et al [29] showed that a flexible 8-week intervention with the EDNA system (3-4 sessions per wk) significantly improved upper extremity function, emphasizing the role of consistent engagement.

Jiaqi Huang, Yixi Wei, Ping Zhou, Xiaokuo He, Hai Li, Xijun Wei

J Med Internet Res 2025;27:e69003