Artificial Intelligence Medical Compendium

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

Showing 18,221 to 18,230 of 214,278 articles

On the use of generative models for demographic inference in malaria vectors from genomic data.

G3 (Bethesda, Md.)
Malaria in sub-Saharan Africa is transmitted by mosquitoes from the Anopheles genus. Efforts to control the spread of malaria have often focused on these vectors, but little is known about the demographic history of populations and species of Anophel... read more 

Deep-Learning Inversion Maps Arbitrary Design Images to Low-Cost, Efficient Nanofabrication.

ACS nano
Rapid, low-cost production of user-defined nanoscale patterns is vital for prototyping in energy, biomedical, and information technologies. Yet top-down lithography is prohibitively expensive, and bottom-up self-assembly affords limited design freedo... read more 

Predictive modeling of injury risk based on body composition and physical fitness performance tests in professional football: A four-year study.

Journal of sports sciences
Preventing sports injuries in professional football enhances players' availability and performance. Machine learning, including artificial neural networks, provides the opportunity to build multivariable prognostic prediction models that can help dev... read more 

Using AI as a teaching partner: enhancing critical thinking and digital literacy in microbiology.

Journal of microbiology & biology education
Artificial intelligence (AI) is rapidly reshaping higher education, offering both opportunities and challenges for teaching and learning. As generative AI tools become increasingly accessible, instructors must balance the benefits of enhanced product... read more 

AI-Based Markerless Computer Vision Framework for Open Surgery Skill Assessment: A Prototype Assessment Framework.

Surgical innovation
BackgroundArtificial intelligence (AI) enables hand motion tracking from standard surgical video recordings; however, translating these data into meaningful performance metrics remains challenging. We evaluated the preliminary validity of a markerles... read more 

Machine-Learning-Driven Molecular Dynamics Unravels Stereoelectronic Switching in Statistical Ensembles of Single-Molecule Junctions.

Journal of the American Chemical Society
Break-junction measurements provide a direct probe of charge transport through single-molecule junctions, but the junction is created and elongated under mechanical loading, leading to variable junction geometries and broad conductance distributions.... read more 

Performance of Statistical and Machine Learning Risk Prediction Models for Advanced Breast Cancers.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
BACKGROUND: Machine learning enables complex risk prediction models, but comparative performance with statistical approaches remains context-dependent. We compared statistical and machine learning models for predicting advanced breast cancer risk. ME... read more 

Crystal Facet Engineering-Photoexcitation-Machine Learning Synergy on Cu2O/CuO Heterojunctions for High-Performance Triethylamine Sensing.

ACS sensors
Triethylamine (TEA), a typical biogenic amine indicative of protein spoilage and a common toxic chemical pollutant, requires highly sensitive detection to ensure both food safety and occupational health. However, existing TEA sensors are often limite... read more 

Comparison of predictive approaches to the dynamics of activated catalytic processes.

Physical chemistry chemical physics : PCCP
We compare two systematic approaches for constructing the kinetic transition network associated with a catalytic reaction, namely reactive global optimization (RGO) and discrete path sampling (DPS). We test convergence of pathways for selected steps ... read more