Artificial Intelligence Medical Compendium

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

Showing 62,921 to 62,930 of 230,760 articles

Predicting Helicoverpa zea (Lepidoptera: Noctuidae) populations in the southern United States.

Environmental entomology Jan 19, 2026
Forecasting insect pest populations before crops are planted can help improve management and reduce pesticide use. Pests with long dispersal potentials and wide host ranges are difficult to predict but often cause losses in crops across broad spatial... read more 
Machine Learning Animals United States Population Dynamics Models, Biological Moths

Multimodal analytical approaches to nanomaterials: TEM, diffraction, image processing, and fractal analysis.

The Analyst Jan 19, 2026
In the field of materials science, using diverse experimental and computational methods is a well-known approach as the most effective route to comprehensive material characterization. Combining high-resolution transmission electron microscopy (TEM) ... read more 

Towards generalisable and equitable artificial intelligence in pathology.

Journal of clinical pathology Jan 19, 2026
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Evaluation of an Artificial Intelligence Defined Lung Nodule Malignancy Score in Incidental Pulmonary Nodules: The CREATE Study.

Mayo Clinic proceedings. Digital health Jan 19, 2026
OBJECTIVE: To evaluate the effectiveness of the artificial intelligence-based qXR lung nodule malignancy score (qXR-LNMS) in detecting high-risk incidental pulmonary nodules (IPNs) on chest X-rays (CXRs). PATIENTS AND METHODS: The CREATE (NCT05817110... read more 

Radiographic Data Segmentation as a Tool in Machine Learning and Deep Learning Artificial Intelligence Algorithms.

Dental clinics of North America Jan 19, 2026
This study reviews radiographic data segmentation as a cornerstone of machine learning (ML) and deep learning (DL) in dentistry. After outlining artificial intelligence (AI), ML, and DL concepts, it highlights convolutional neural networks-driven tas... read more 

Machine learning for triage of strokes with large vessel occlusion using photoplethysmography biomarkers.

Physiological measurement Jan 19, 2026
Objective.Large vessel occlusion (LVO) stroke presents a major challenge in clinical practice due to the potential for poor outcomes with delayed treatment. Treatment for LVO involves highly specialized care, in particular endovascular thrombectomy, ... read more 
Humans Machine Learning Biomarkers Female Aged Aged, 80 and over Male Middle Aged Photoplethysmography Triage Stroke

Validation of uPath HER2 dual-colour dual in-situ hybridisation image analysis tool for HER2/neu testing in breast cancer.

Journal of clinical pathology Jan 19, 2026
AIMS: HER2/neu gene is amplified in 15%-20% of invasive breast cancers (IBCs), serving as critical prognostic and predictive marker. HER2-targeted therapies have improved outcomes for HER2-positive patients, highlighting the importance of accurate as... read more 
Humans Algorithms Retrospective Studies Female Reproducibility of Results Aged Breast Neoplasms Biomarkers, Tumor Middle Aged Image Processing, Computer-Assisted Predictive Value of Tests In Situ Hybridization, Fluorescence Image Interpretation, Computer-Assisted Observer Variation In Situ Hybridization Erb-b2 Receptor Tyrosine Kinases

STRUCT2SEQ: RNA INVERSE FOLDING WITH DEEP Q-LEARNING

bioRxiv Jan 18, 2026
RNA molecules play critical roles in biology and therapeutics, with their function intimately tied to their secondary structure. Designing RNA sequences that reliably fold into desired secondary structures, especially those with complex pseudoknots, ... read more 
biophysics

Fundamental limitations of genomic language models for realistic sequence generation

bioRxiv Jan 18, 2026
Large language models (LLMs) have shown remarkable success in natural language processing, prompting interest in their application to genomic sequence analysis. Genomic Language Models based on similar architectures offer a promising avenue for synth... read more 
synthetic biology

SE3Bind: SE(3)-equivariant model for antibody-antigen binding affinity prediction

bioRxiv Jan 18, 2026
Predicting antibody-antigen binding affinity is critical for therapeutic development, but machine learning-based approaches to the problem are typically hampered by the small amount of available structural and affinity data. We introduce SE3Bind, an ... read more 
bioinformatics
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