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Using Machine Learning to Predict-Then-Optimize Elective Orthopedic Surgery Scheduling to Improve Operating Room Utilization: Retrospective Study.

JMIR medical informatics
BACKGROUND: Total knee and hip arthroplasty (TKA and THA) are among the most performed elective procedures. Rising demand and the resource-intensive nature of these procedures have contributed to longer wait times despite significant health care inve...

Biological Age Estimation From the Age Gap Using Deep Learning Integrating Morbidity and Mortality: Model Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Biological age (BA) is increasingly recognized as a valuable alternative to chronological age (CA) for assessing an individual's health and aging status. However, existing models are based on limited clinical parameters and have not thoro...

Health Care Professionals' Experiences Regarding Facilitators of and Barriers to Sustained Use of Social Robot Ivy for People With Intellectual Disabilities: Qualitative Interview Study.

Journal of medical Internet research
BACKGROUND: Labor shortages in health care pose significant challenges to sustaining high-quality care for people with intellectual disabilities. Social robots show promise in supporting both people with intellectual disabilities and their health car...

Exploring Women's Perceptions of Traditional Mammography and the Concept of AI-Driven Thermography to Improve the Breast Cancer Screening Journey: Mixed Methods Study.

JMIR cancer
BACKGROUND: Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, rad...

Predicting Unplanned Readmission Risk in Patients With Cirrhosis: Complication-Aware Dynamic Classifier Selection Approach.

JMIR medical informatics
BACKGROUND: Cirrhosis is a leading cause of noncancer deaths in gastrointestinal diseases, resulting in high hospitalization and readmission rates. Early identification of high-risk patients is vital for proactive interventions and improving health c...

Observing a robot peer's failures facilitates students' classroom learning.

Science robotics
According to productive failure (PF) theory, experiencing failure during problem-solving can enhance students' knowledge acquisition in subsequent instruction. However, challenging students with problems beyond their current capabilities may strain t...

Robotic reading companions can mitigate oral reading anxiety in children.

Science robotics
Reading fluency is a vital building block for developing literacy, yet the best way to practice fluency-reading aloud-can cause anxiety severe enough to inhibit literacy development in ways that can have an adverse effect on students through adulthoo...

Decoding binocular color differences via EEG signals: linking ERP dynamics to chromatic disparity in CIELAB space.

Experimental brain research
This study explores how differences in colors presented separately to each eye (binocular color differences) can be identified through EEG signals, a method of recording electrical activity from the brain. Four distinct levels of green-red color diff...

Investigating the role of AI explanations in lay individuals' comprehension of radiology reports: A metacognition lens.

PloS one
While there has been extensive research on techniques for explainable artificial intelligence (XAI) to enhance AI recommendations, the metacognitive processes in interacting with AI explanations remain underexplored. This study examines how AI explan...