AI Medical Compendium Journal:
Computer methods and programs in biomedicine

Showing 1 to 10 of 844 articles

Investigating the interpretability of ChatGPT in mental health counseling: An analysis of artificial intelligence generated content differentiation.

Computer methods and programs in biomedicine
The global impact of COVID-19 has caused a significant rise in the demand for psychological counseling services, creating pressure on existing mental health professionals. Large language models (LLM), like ChatGPT, are considered a novel solution for...

Predicting metabolite-disease associations based on dynamic adaptive feature learning architecture.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In recent years, the association between metabolites and complex human diseases has increasingly been recognized as a major research focus. Traditional wet-lab experiments are considered time-consuming and labor-intensive, w...

Understanding deep learning models for Length of Stay prediction on critically ill patients through latent space visualization.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Continuous, real-time monitoring of Length of Stay (LoS) for critically ill patients in Intensive Care Units (ICUs) is essential for anticipating patient needs, reduce the risk of adverse events, optimize resource allocation...

Deep learning techniques for automated coronary artery segmentation and coronary artery disease detection: A systematic review of the last decade (2013-2024).

Computer methods and programs in biomedicine
BACKGROUND: Coronary artery disease (CAD) is the most common cardiovascular disease, exacting high morbidity and mortality worldwide. CAD is detected on coronary artery imaging; coronary artery segmentation (CAS) of the images is essential for corona...

The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Diabetes is a chronic disease characterised by a high risk of developing diabetic nephropathy. The early identification of individuals at heightened risk of such complications or their exacerbation can be crucial to set a co...

Causal insights from clinical information in radiology: Enhancing future multimodal AI development.

Computer methods and programs in biomedicine
PURPOSE: This study investigates the causal mechanisms underlying radiology report generation by analyzing how clinical information and prior imaging examinations contribute to annotation shifts. We systematically estimate why and how biases manifest...

Multi-positive contrastive learning-based cross-attention model for T cell receptor-antigen binding prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: T cells play a vital role in the immune system by recognizing and eliminating infected or cancerous cells, thus driving adaptive immune responses. Their activation is triggered by the binding of T cell receptors (TCRs) to ep...

Multi-task learning for joint prediction of breast cancer histological indicators in dynamic contrast-enhanced magnetic resonance imaging.

Computer methods and programs in biomedicine
OBJECTIVES: Achieving efficient analysis of multiple pathological indicators has great significance for breast cancer prognosis and therapeutic decision-making. In this study, we aim to explore a deep multi-task learning (MTL) framework for collabora...

Development of patient-specific apparent blood viscosity predictive models for computational fluid dynamics analysis of intracranial aneurysms with machine learning approaches.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: A model to predict patient-specific apparent viscosity as a computational condition in computational fluid dynamics (CFD) analysis, which is used in research on intracranial aneurysms, is important. The purpose of this stud...

Evaluation of blood- and urine-derived biomarkers for machine learning prediction models of osteoarthritis in elderly patients: A feasibility study.

Computer methods and programs in biomedicine
BACKGROUND: Osteoarthritis (OA) is a common degenerative joint disease, particularly affecting individuals aged >50 years. It deteriorates quality of life and restricts physical activity in the elderly. Early diagnosis of OA is crucial for effective ...