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O-GEST: Overground gait events detector using b-spline-based geometric models for marker-based and markerless analysis.
Journal of biomechanics
Jun 6, 2025
Accurate gait events detection is imperative for reliable assessment of normal and pathological gaits. However, this detection becomes challenging in the absence of force plates. Hence, this research introduces two geometric models integrated into an...
A multi-site randomized clinical trial of socially assistive robots on engaging older adults with cognitive impairment residing in long-term care settings: A protocol paper.
Contemporary clinical trials
Jun 6, 2025
Apathy is common in persons with dementias, especially those in long-term care facilities (LTCs). Few pharmacologic options exist; a major strategy is to foster engagement in social, physical, and cognitive activities, but requires extensive personne...
Cone-beam computed tomography-based online adaptive radiotherapy of esophageal cancer in the neoadjuvant setting: Dosimetric analysis, toxicity and treatment response.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jun 6, 2025
BACKGROUND AND PURPOSE: Chemoradiotherapy (CRT) followed by surgery is a treatment option for esophageal cancer (EC). However, concerns persist regarding cardiopulmonary toxicity and inconsistent daily target coverage due to anatomical changes. To ad...
Leveraging pulse wave signal properties for coronary artery calcification screening in CKD patients.
Computers in biology and medicine
Jun 6, 2025
BACKGROUND AND AIMS: Chronic kidney disease (CKD) patients are particularly susceptible to coronary atherosclerosis, which can be assessed using computed tomography (CT)-based coronary artery calcium (CAC) score. However, such a costly examination mi...
Evaluating the relationship between environmental chemicals and obesity: Evidence from a machine learning perspective.
Ecotoxicology and environmental safety
Jun 6, 2025
Environmental chemicals are increasingly recognized as important contributors to obesity, yet the number of studies evaluating this relationship remains insufficient. This study aimed to investigate these associations using interpretable machine lear...
How mental health status and attitudes toward mental health shape AI Acceptance in psychosocial care: a cross-sectional analysis.
BMC psychology
Jun 6, 2025
INTRODUCTION: Artificial Intelligence (AI) has become part of our everyday lives and is also increasingly applied in psychosocial healthcare as it can enhance it, make it more accessible, and reduce barriers for help seeking. User behaviour and readi...
Predicting rapid kidney function decline in middle-aged and elderly Chinese adults using machine learning techniques.
BMC medical informatics and decision making
Jun 6, 2025
The rapid decline of kidney function in middle-aged and elderly people has become an increasingly serious public health problem. Machine learning (ML) technology has substantial potential to disease prediction. The present study use dataset from the ...
Histopathologic deep learning model for predicting tumor response to hepatic arterial infusion chemotherapy plus TKIs and ICIs in large hepatocellular carcinoma.
Cancer imaging : the official publication of the International Cancer Imaging Society
Jun 6, 2025
BACKGROUND: While triplet therapy (HTI), which combines hepatic arterial infusion chemotherapy (HAIC) with tyrosine kinase inhibitors and immune checkpoint inhibitors, is widely used in the treatment of large hepatocellular carcinoma (HCC), there are...
Machine learning method based on radiomics help differentiate posterior pituitary tumors from pituitary neuroendocrine tumors and craniopharyngioma.
Scientific reports
Jun 6, 2025
Posterior pituitary tumors (PPTs) are rare neoplasms, but easily misdiagnosed as pituitary neuroendocrine tumor (PitNET) and craniopharyngioma. This study aimed to differentiate PPTs from PitNET and craniopharyngioma using a machine learning method b...
The value of intratumoral and peritumoral ultrasound radiomics model constructed using multiple machine learning algorithms for non-mass breast cancer.
Scientific reports
Jun 6, 2025
To investigate the diagnostic capability of multiple machine learning algorithms combined with intratumoral and peritumoral ultrasound radiomics models for non-massive breast cancer in dense breast backgrounds. Manual segmentation of ultrasound image...
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