Artificial Intelligence Medical Compendium

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

Showing 35,691 to 35,700 of 222,841 articles

Implementing drug data exclusivity in China: A comparative analysis with global practices.

Drug discovery today Apr 3, 2026
This article provides a comprehensive overview and comparative analysis of China's forthcoming drug data exclusivity system, contextualizing it within global frameworks. It presents the current data exclusivity regimes of the United States, Canada, t... read more 

Bipolar disorder relapse detection and prediction using smartwatches. A pilot study for machine learning models using anomaly detection methods.

Journal of affective disorders Apr 3, 2026
BACKGROUND: Bipolar disorder (BD) is a chronic mental illness with recurrent mood episodes, with up to 70% of patients relapsing within two years. Early detection of prodromal symptoms is critical for timely intervention but remains challenging. Wear... read more 

High-Throughput Image-Based Pupal Sex Classification in Aedes aegypti Using Convolutional Neural Network Models for Sterile Insect Technique Applications.

Acta tropica Apr 3, 2026
Aedes aegypti, the primary vector of dengue, yellow fever, Zika, and chikungunya, poses serious public health threats, especially in tropical regions. With limited vaccine availability, innovative control strategies like the Sterile Insect Technique ... read more 

Artificial Intelligence-assisted Mining of Polyethylene Terephthalate Hydrolases.

New biotechnology Apr 3, 2026
Polyethylene terephthalate (PET) hydrolases efficiently hydrolyze the ester bonds in PET, converting it into valuable monomers or oligomers, offering a sustainable biological solution to global PET plastic pollution. However, the large-scale developm... read more 

Deep learning and image processing for high-throughput udder phenotyping in dairy cows.

Journal of dairy science Apr 3, 2026
Udder conformation is a crucial phenotype in dairy cows as it relates to their health and productivity, particularly in Automated Milking Systems (AMS). As such, this project aims to (1) develop an automated pipeline that extracts udder phenotypes fr... read more 

Deep and High-Throughput Proteomic Atlas of Chinese Bovine Colostrum Reveals Regional Signatures.

Journal of dairy science Apr 3, 2026
Bovine colostrum (BC) is essential for neonatal survival and human health, owing to its rich bioactive content. However, highly abundant proteins constrain the proteome depth of BC. By integrating magnetic nanoparticle enrichment of low-abundance pro... read more 

Predicting Staphylococcus aureus spa Types Using MALDI-TOF Mass Spectrometry and Machine Learning.

Journal of dairy science Apr 3, 2026
Staphylococcus aureus is a leading cause of intramammary infections (IMI) in Canadian dairy herds and is frequently isolated from both clinical and subclinical mastitis cases. Persistent IMI caused by S. aureus are of particular concern, as they are ... read more 

Machine Learning-Driven Classification of Bioactive Peptides and Their Molecular Basis for Sour Taste Perception.

Journal of dairy science Apr 3, 2026
Bioactive peptides derived from dairy proteins are increasingly recognized for their dual capacity to enhance sensory attributes and provide health-promoting functions. In fermented dairy products such as yogurt, proteolysis releases a diverse array ... read more 

Beyond literacy to clinical competency: A framework for integrating generative AI into nursing education.

Nurse education today Apr 3, 2026
PROBLEM: Health systems are rapidly integrating generative artificial intelligence (GenAI) into clinical workflows, introducing safety risks including hallucinations and automation bias. These risks threaten patient safety when frontline nurses lack ... read more 

An artificial intelligence model for accurate drug-target affinity prediction in medicinal chemistry.

European journal of medicinal chemistry Apr 3, 2026
Predicting Drug-Target Affinity (DTA) with high fidelity is critical for accelerating hit-to-lead optimization and understanding mechanism of action. While deep learning has transformed this field, current approaches often struggle with the effective... read more 
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