Cryptorchidism, a common male reproductive disorder characterized by undescended testes, is associated with infertility and increased cancer risk. While its etiology remains incompletely understood, accumulating evidence suggests that immune-inflamma...
European journal of psychotraumatology
Jul 28, 2025
Perceived Social support has been consistently shown to reduce depressive symptoms among military personnel. However, limited research has explored how different types of support, emotional, informational, and instrumental, from multiple sources uni...
INTRODUCTION: Diagnosing pulmonary tuberculosis (PTB) in children is challenging owing to paucibacillary disease, non-specific symptoms and signs and challenges in microbiological confirmation. Chest X-ray (CXR) interpretation is fundamental for diag...
BACKGROUND: Colleges have turned to digital mental health interventions to meet the increasing mental health treatment needs of their students. Among these, chatbots stand out as artificial intelligence-driven tools capable of engaging in human-like ...
BACKGROUND: Recent advances in histology scanning technology and Artificial Intelligence (AI) offer great opportunities to support cancer diagnosis. The inability to interpret the extracted features and model predictions is one of the major issues li...
BACKGROUND: Incorrectly placed endotracheal tubes (ETTs) can lead to serious clinical harm. Studies have demonstrated the potential for artificial intelligence (AI)-led algorithms to detect ETT placement on chest X-Ray (CXR) images, however their eff...
BMC medical informatics and decision making
Jul 28, 2025
INTRODUCTION: Emergency departments (EDs) are critical for ensuring timely patient care, especially in triage, where accurate prioritisation is essential for patient safety and resource utilisation. Building on previous research, this study leverages...
BMC medical informatics and decision making
Jul 28, 2025
BACKGROUND: Lumbar spinal stenosis is one of the most common surgery-requiring conditions of the spine in the aged population. As elderly patients often present with multiple comorbidities and limited physiological reserve, individualized risk assess...
OBJECTIVE: This study aimed to develop an interpretable machine learning model integrating delayed-phase contrast-enhanced CT radiomics with clinical features for noninvasive prediction of pathological grading in appendiceal pseudomyxoma peritonei (P...
PURPOSE: To predict the 1p/19q molecular status of Lower-grade glioma (LGG) patients nondestructively, this study developed a deep learning (DL) approach using radiomic to provide a potential decision aid for clinical determination of molecular strat...
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