Artificial Intelligence Medical Compendium

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

Showing 2,391 to 2,400 of 235,381 articles

Reliability of Machine Learning Approaches Towards the Identification of Novel PI4KIIIβ Inhibitors.

Current topics in medicinal chemistry
INTRODUCTION: The type III Phosphatidylinositol 4-kinase (PI4KIIIβ) serves as a key host factor that mediates the replication of RNA viruses and is involved in essential membrane trafficking events. The development of PI4KIIIβ-specific inhibitors cou... read more 

Synthetic Strategies Toward Naturally Occurring α-Pyrones: A Review of Total Syntheses and Methodological Advances.

Mini reviews in medicinal chemistry
α-Pyrones constitute an important class of natural products widely distributed in plants, fungi, bacteria, and marine organisms, exhibiting diverse biological activities, including antimicrobial, anticancer, anti-inflammatory, antiparasitic, and phyt... read more 

Functional Near-Infrared Spectroscopy Combined with Machine Learning for Exploratory Classification of Autism Spectrum Disorder in Young Children.

Journal of visualized experiments : JoVE
Early identification of autism spectrum disorder (ASD) may facilitate timely intervention, while diagnosis remains clinically based. This exploratory study evaluated fNIRS-derived features using multiple machine-learning algorithms to compare observe... read more 

SecureHealthKey+: Integrating Explainable TinyML Anomaly Detection Into Lightweight Authentication Protocols in IoT-Enabled Healthcare Systems.

Journal of visualized experiments : JoVE
The Internet of Medical Things (IoMT) and Wireless Body Area Networks (WBANs) enable real-time, remote, and continuous patient monitoring but remain vulnerable to cyber-physical attacks, including unauthorized device access, replay, man-in-the-middle... read more 

Adaptive Dual-Attention DenseNet for Object-Aware Two-Stage Industrial Defect Detection.

Journal of visualized experiments : JoVE
Industrial visual anomaly detection is crucial in intelligent manufacturing to achieve automated quality inspection with low dependency on manual inspection. Nevertheless, traditional single-stage deep learning methods struggle to detect both object ... read more 

Machine Learning, Radiomics, and Clinical Models Predicting Checkpoint Inhibitor Pneumonitis in Lung Cancer: A Systematic Review and Meta-analysis.

Journal of visualized experiments : JoVE
Checkpoint inhibitor pneumonitis (CIP) is a potentially fatal immune-related adverse event of immune checkpoint inhibitor (ICI) therapy in lung cancer, and many machine-learning (ML), computed tomography (CT) radiomics, deep-learning, and clinical mo... read more 

Curriculum-Aligned Conversational AI to Support Pathology Self-Directed Learning in Preclinical Medical Students: A Crossover Randomized Pilot Study.

JMIR medical education
BACKGROUND: Artificial intelligence (AI) is reshaping the landscape of medical education, yet the widespread adoption of general-purpose AI tools in student learning raises substantial concerns about curricular alignment, information accuracy, and th... read more 

Comprehensive multi-omics analysis identifies BTG2 as a potential regulator of radiotherapy response in lung adenocarcinoma.

Neoplasia (New York, N.Y.)
Lung adenocarcinoma (LUAD) is one of the most common malignancies worldwide. However, patients exhibit heterogeneous responses to radiotherapy, and a subset of individuals develops resistance, which severely compromises clinical outcomes. The underly... read more 

Unraveling membrane protein conformational landscapes: Enhanced sampling, membrane regulation, and artificial intelligence-assisted simulation.

Current opinion in structural biology
Membrane proteins undergo functionally essential conformational transitions that couple local chemical events and changes in the membrane environment to large-scale structural rearrangements. These transitions are often difficult to capture with conv... read more 

Enhanced two-stage cascaded network for high-precision stopping power ratio and functional image generation from conventional CT.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
PURPOSE: Accurate stopping power ratio (SPR) estimation is essential for proton therapy dose calculation; however, SPR and related functional images-electron density (ED), effective atomic number (Zeff), and iodine concentration (IC)-currently requir... read more