Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 64,941 to 64,950 of 231,605 articles

Soil microbial diversity, stability, and function are enhanced by cover cropping: A machine learning-based pooled analysis of Mississippi agroecosystems.

The Science of the total environment
Cover cropping has emerged as a pivotal strategy to enhance soil health and microbiome functionality across diverse agroecosystems. However, the extent to which cover crops reshape microbial diversity, composition, functional capacity, and ecological... read more 

Integrating AI design tools into traditional design workflows: A study on collaborative tool usage willingness based on the Push-Pull-Mooring framework.

Acta psychologica
In the context of rapid AI development, designers are increasingly integrating AI tools into traditional workflows, forming a collaborative rather than substitutive mode of tool usage. Grounded in the Push-Pull-Mooring (PPM) framework, this study inv... read more 

The power of beliefs: How Generative Artificial Intelligence (GenAI) influences academic performance.

Acta psychologica
The application of Generative Artificial Intelligence (GenAI) in higher education is expanding rapidly. However, little research focusses on the influence of students' beliefs on the application effectiveness of GenAI and their academic performance. ... read more 

Usability of quantitative atlas measurements from computed tomography images for sex estimation: A machine learning approach.

Morphologie : bulletin de l'Association des anatomistes
Sex estimation plays a critical role in forensic identification, missing person identification, and forensic investigations. This study aimed to evaluate the usability of quantitative metric measurements obtained from computed tomography (CT) images ... read more 

From data to diagnosis: A comprehensive review of machine learning-driven wearable sensors in healthcare.

Bioelectrochemistry (Amsterdam, Netherlands)
The integration of machine learning (ML) with advanced wearable sensor technologies is revolutionizing healthcare by enabling real-time, intelligent monitoring of physiological parameters such as electrocardiogram (ECG), blood glucose, and respirator... read more 

RLBindDeep: A ResNet-LSTM based novel framework for protein-ligand binding affinity prediction.

Journal of molecular graphics & modelling
The prediction of the binding affinity of proteins and ligands in computational drug discovery with high accuracy is critical when evaluating the effectiveness of potential therapeutic compounds. This research work introduces RLBindDeep, a novel deep... read more 

Molreac-Oxi: An end-to-end deep learning-quantum chemistry platform for •OH reactivity (kOH), pathways, and active-site insight.

Environmental research
To address the long-standing challenge of efficiently evaluating reaction rate constants (kOH) for pollutant-hydroxyl radical (•OH) systems in environmental pollution control, a hybrid meta-model framework is introduced that fuses deep pretrained mod... read more 

Predicting postpartum glucose intolerance in women with gestational diabetes mellitus in primary care: A machine learning approach using XGBoost and SHAP values.

Diabetes research and clinical practice
OBJECTIVE(S): To develop and internally validate an interpretable machine learning model using eXtreme Gradient Boosting (XGBoost) and Shapley Additive exPlanations (SHAP) to predict postpartum glucose intolerance among women with GDM using routine a... read more 

FG-DDI: Functional group-aware graph neural networks for drug-drug interaction prediction.

Journal of biomedical informatics
OBJECTIVE: We aim to improve Drug-Drug Interactions (DDIs) by explicitly injecting medicinal-chemistry knowledge of functional groups (FGs) into graph neural network (GNN) message passing, in both transductive and inductive settings. Our goal is to (... read more