AI Medical Compendium Journal:
Computers in biology and medicine

Showing 61 to 70 of 1779 articles

Enhancing osteoporosis risk prediction using machine learning: A holistic approach integrating biomarkers and clinical data.

Computers in biology and medicine
Osteoporosis (OP) affects approximately 18 % of the global population, with osteoporosis-associated fractures impacting up to 37 million people annually. While dual-energy X-ray absorptiometry (DXA) remains the gold standard for diagnosis, its limita...

Navigating nutrients: A scoping review on real-time food nutrition classification and recommendation systems.

Computers in biology and medicine
In an era where fast-paced lifestyles often conflict with the pursuit of healthy eating, the demand for innovative solutions to aid nutritional decision-making has never been more pressing. Real-time food nutrition classification and recommendation s...

Molecular landscape of endometrioid Cancer: Integrating multiomics and deep learning for personalized survival prediction.

Computers in biology and medicine
BACKGROUND: The endometrioid subtype of endometrial cancer is a significant health concern for women, making it crucial to study the factors influencing patient outcomes.

An enhanced harmonic densely connected hybrid transformer network architecture for chronic wound segmentation utilising multi-colour space tensor merging.

Computers in biology and medicine
Chronic wounds and associated complications present ever growing burdens for clinics and hospitals world wide. Venous, arterial, diabetic, and pressure wounds are becoming increasingly common globally. These conditions can result in highly debilitati...

Multimodal large language models as assistance for evaluation of thyroid-associated ophthalmopathy.

Computers in biology and medicine
This study evaluated the potential of multimodal AI chatbots, specifically ChatGPT-4o, in assessing thyroid-associated ophthalmopathy (TAO) through the Clinical Activity Score (CAS). Using publicly available case reports and datasets, ChatGPT-4o was ...

Deep learning meets marine biology: Optimized fused features and LIME-driven insights for automated plankton classification.

Computers in biology and medicine
Plankton are microorganisms that play an important role in marine food webs as primary producers in the trophic web. Traditional plankton identification methods using manual microscopy and sampling are time-consuming, labor-intensive, and prone to er...

DeepValve: The first automatic detection pipeline for the mitral valve in Cardiac Magnetic Resonance imaging.

Computers in biology and medicine
Mitral valve (MV) assessment is key to diagnosing valvular disease and to addressing its serious downstream complications. Cardiac magnetic resonance (CMR) has become an essential diagnostic tool in MV disease, offering detailed views of the valve st...

EB-YOLO:An efficient and lightweight blood cell detector based on the YOLO algorithm.

Computers in biology and medicine
Blood cell detection is an important part of medical diagnosis. Object detection is trending for blood cell analysis, with research focusing on high-precision neural network models. However, these models have complex architectures and high computatio...

Cancer type and survival prediction based on transcriptomic feature map.

Computers in biology and medicine
This study achieved cancer type and survival time prediction by transforming transcriptomic features into feature maps and employing deep learning models. Using transcriptomic data from 27 cancer types and survival data from 10 types in the TCGA data...

CellOMaps: A compact representation for robust classification of lung adenocarcinoma growth patterns.

Computers in biology and medicine
Lung adenocarcinoma (LUAD) is a morphologically heterogeneous disease, characterized by five primary histological growth patterns. The classification of such patterns is crucial due to their direct relation to prognosis but the high subjectivity and ...