BACKGROUND: People experiencing homelessness have worse oral health outcomes and a notable health informational asymmetry compared to the general population. Screening programs present a viable option for this population; however, barriers to access,...
Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are essential clinical cross-sectional imaging techniques for diagnosing complex conditions. However, large 3D datasets with annotations for deep learning are scarce. While methods like DI...
BACKGROUND: Heart failure and atrial fibrillation (HF-AF) frequently coexist, resulting in complex interactions that substantially elevate mortality risk. This study aimed to develop and validate a machine learning (ML) model predicting the 3-year al...
The integration of machine learning (ML) and deep learning models in suicide risk assessment has advanced significantly in recent years. In this study, we utilized ML in a case-control design, we predicted completed suicides using publicly available,...
BACKGROUND: Integrating artificial intelligence (AI), especially large language models (LLM) into oncology has potential benefits, yet medical oncologists' knowledge, attitudes, and ethical concerns remain unclear. Understanding these perspectives is...
BACKGROUND: Mental health is an essential element of life. However, existing mental health services face challenges in utilization due to issues such as societal prejudices and a shortage of counselors. Mobile health is gaining attention as an altern...
Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting millions worldwide, leading to inflammation, joint damage, and reduced quality of life. Although biological disease-modifying antirheumatic drugs (bDMARDs) are effective, they are co...
OBJECTIVES: This study aimed to develop and validate a machine learning (ML) model that integrates radiomics and conventional radiological features to predict the success of single-session extracorporeal shock wave lithotripsy (ESWL) for ureteral sto...
BACKGROUND: Managing multiple long-term conditions (MLTC) is complex. Clinical management guidelines are typically focused on individual conditions and lack a robust evidence base for patients with MLTC. MLTC management is largely delivered in primar...
OBJECTIVE: With survival steadily improving among people living with HIV(PLWH), quality of life (QoL) has emerged as the ultimate benchmark of therapeutic success. We therefore aimed to develop and validate machine learning models that predict QoL tr...
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