Disability and rehabilitation. Assistive technology
Apr 12, 2025
PURPOSE: This study explores the relationship between happiness and well-being, with a particular focus on how Artificial Intelligence (AI) serves as a catalyst for enhancing the quality of life of individuals with disabilities. The research aims to ...
The Journal of hand surgery, European volume
Apr 12, 2025
This study sought to establish and validate a machine learning-based multi-sequence MRI radiomics model for predicting postoperative complications in patients with peripheral nerve sheath tumours. We conducted a retrospective analysis of 303 patients...
Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
Apr 12, 2025
PURPOSE: To construct and validate a magnetic resonance imaging (MRI) radiomics combined with delta-radiomics and clinical information (C) model for predicting pathological complete response (pCR) in patients with locally advanced rectal cancer (LARC...
OBJECTIVE: To develop an objective ensemble machine learning model combining clinical features and quantitative EEG metrics (phase locking value [PLV] and multiscale sample entropy [MSE]) to support accurate diagnosis of juvenile myoclonic epilepsy (...
The countermovement jump (CMJ) assessment is widely employed for monitoring sports performance, traditionally relying on heavy and expensive force plates to extract performance variables like jump height and peak force. Inertial measurement unit (IMU...
The gait analysis has been applied in many fields, such as the assessment of falling, force evaluation in sports, and gait disorder detection for neuromuscular diseases. Its main recording techniques include video cameras and wearable sensors. Howeve...
Schizophrenia (SZ) and bipolar disorder (BD) pose diagnostic challenges due to overlapping clinical symptoms and genetic factors, often resulting in misdiagnosis and suboptimal treatment outcomes. This study aimed to identify EEG-based biomarkers tha...
The exploration of deep learning techniques for predicting various biological characteristics of endometrial cancer (EC) is of significant importance. The objective of this study was to develop an optimized radiomics scheme combining multiparametric ...
PURPOSE: To develop machine learning models that are driven by Gd-EOB-DTPA-MRI features for the preoperative prediction of early recurrence in HCC and compare them to the previously proposed ERASL-pre method.
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Apr 11, 2025
OBJECTIVE: To evaluate the diagnostic value of shear wave elastography (SWE) in assessing endometriomas and its correlation with clinical symptoms. Furthermore, the study investigates the use of machine learning (ML) models to predict clinical outcom...
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