This study intends to empower English as a Foreign Language (EFL) teachers' perceptions of generative artificial intelligence (AI)-mediated self-professionalism in engagement, attitudes, constraints, and solutions. Employing the mixed methods researc...
Schizophrenia (SZ) and Bipolar disorder (BD) share genetic and cerebral abnormalities, supporting an expanded continuum hypothesis. In this paper, we aim to better characterize differences and commonalities of gray and white matter features between S...
International journal of medical informatics
Jun 21, 2025
OBJECTIVE: Develop a two-stage, machine learning-based thrombolysis risk stratification model from existing medical datasets and electronic health records to predict the risk of early hemorrhagic transformation(HT) and in-hospital mortality(IM) follo...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jun 21, 2025
PURPOSE: To investigate the feasibility and accuracy of using deep learning and dosiomics features, as well as their combination with dose-volume histogram (DVH) parameters and clinical factors to predict grade 4 radiation-induced lymphopenia (G4RIL)...
Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Jun 20, 2025
PURPOSE: Pulmonary valve regurgitation after repaired Tetralogy of Fallot (TOF) or double-outlet right ventricle (DORV) causes hypertrophy and papillary muscle enlargement. Cardiac magnetic resonance imaging (CMR) can evaluate the right ventricular (...
Suicide prevention is currently a global public health priority, since suicide has been a prevalent cause of death or potential loss of life. Multiple factors contribute to suicide risk, such as depression and a history of attempted suicide among oth...
BACKGROUND: High-resolution computed tomography (HRCT) is helpful for diagnosing interstitial lung diseases (ILD), but it largely depends on the experience of physicians. Herein, our study aims to develop a deep-learning-based classification model to...
This study aims to develop a robust and accurate model to forecast 30-day readmissions for patients with diabetes by leveraging machine learning techniques. Diabetes, being a chronic condition with complex care needs, often leads to frequent hospital...
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