BACKGROUND: Effective communication is fundamental to high-quality health care delivery, influencing patient satisfaction, adherence to treatment plans, and clinical outcomes. However, communication skills training for medical undergraduates often fa...
Advances in radiotherapy have increased treatment plan complexity, making manual quality evaluation more subjective and variable. While deep learning approaches offer automation in planning, evaluation remains a manual bottleneck. Existing indices ev...
Assessing the efficacy of radiotherapy in patients with high-grade gliomas (HGGs) is challenging due to the occurrence of pseudo-progression and radionecrosis. This study introduces a directed graph network leveraging MR image features at multiple ti...
OBJECTIVE: Mild cognitive impairment (MCI) signals cognitive decline beyond normal aging and increases dementia risk. Early identification enables preventative interventions, yet many patients in primary care go undetected. This study examines whethe...
Early identification of students' mental health issues has become an urgent priority in education and public health. However, existing studies often rely on questionnaire-based assessments or traditional machine learning models, which are limited by ...
Early triage of trauma patients requiring massive transfusion (MT) may help to marshal appropriate resources and improve treatment and outcome. Artificial intelligence (AI) and machine learning (ML) offer theoretical advantages compared to convention...
Journal of the American Chemical Society
Oct 23, 2025
Aptamers are powerful synthetic recognition elements for biosensing, yet their application in complex biofluids, such as human serum, is critically limited by enzymatic degradation. To overcome this fundamental challenge, we introduce a novel analyti...
PURPOSE: To propose a multi-parametric ultrasound imaging-based deep learning method for accurately classifying metastatic and non-metastatic axillary lymph nodes in breast cancer patients.
BACKGROUND AND PURPOSE: This study aims to develop a robust and user-friendly prediction model for radiation-induced hypothyroidism (RIHT) in nasopharyngeal carcinoma (NPC) patients.
BMC medical informatics and decision making
Oct 23, 2025
BACKGROUND: Traditional diagnostic methods used by neurosurgeons are limited in their ability to address complex interactions. These limitations have necessitated the use of advanced artificial intelligence approaches capable of analyzing multidimens...
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