BACKGROUND: Coronary computed tomography angiography (CCTA) has emerged as the first-line noninvasive imaging test for patients at high risk of coronary artery disease (CAD). When combined with machine learning (ML), it provides more valid evidence i...
Clinical cancer research : an official journal of the American Association for Cancer Research
Jun 13, 2025
PURPOSE: Although the association between cytotoxic T lymphocytes and favorable prognosis in colorectal cancer is well established, the prognostic significance of B lymphocytes remains more ambiguous. This study aimed to assess the characteristics an...
This study presents a machine learning model to predict renal function decline following minimally-invasive partial nephrectomy. Using a dataset of 556 patients treated between 2015 and 2023, the model incorporated patient, tumor, and intraoperative ...
OBJECTIVE: Stroke is a leading cause of morbidity and disability worldwide. Post-stroke cognitive impairment (PSCI) significantly affects long-term prognosis in acute anterior circulation large-vessel occlusion stroke (LVO-AIS). This study aims to de...
Osteoarthritis is a multifactorial condition marked by the gradual deterioration of joint cartilage, synovial inflammation, alterations in the subchondral bone and changes in the surrounding soft tissues. Clinical assessments and patient-reported out...
Acute and chronic ischemic cardiomyopathy (ICM) still represents a leading cause of morbidity and mortality. Cardiac magnetic resonance (CMR) imaging plays a central role in the diagnosis and management of ICM, offering detailed visualization of card...
INTRODUCTION: Sarcopenia, or the loss of muscle quality and quantity, has been associated with poor clinical outcomes in liver transplantation such as infection, increased length of stay, and increased patient mortality. Abdominal computed tomography...
Journal of cellular and molecular medicine
Jun 1, 2025
Oral cancer is among the most prevalent malignant tumours worldwide; prognosis can be affected by several factors, including molecular subtypes, immune microenvironment and clinical characteristics. In this study, we aimed to apply machine learning m...
Brain Tumours are highly complex, particularly when it comes to their initial and accurate diagnosis, as this determines patient prognosis. Conventional methods rely on MRI and CT scans and employ generic machine learning techniques, which are heavil...
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