Artificial Intelligence Medical Compendium

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

Showing 4,101 to 4,110 of 173,463 articles

SATURN: Autoregressive Image Generation Guided by Scene Graphs

arXiv Aug 20, 2025
State-of-the-art text-to-image models excel at photorealistic rendering but often struggle to capture the layout and object relationships implied by complex prompts. Scene graphs provide a natural structural prior, yet previous graph-guided approac... read more 
Computer Vision and Pattern Recognition

Predicting hydrocarbon presence in marine cold seep sediments using machine learning models trained with benthic bacterial 16S rRNA taxonomy.

Microbiology spectrum Aug 20, 2025
UNLABELLED: Hydrocarbon seepage in marine sediments exerts selective pressure on benthic microbiomes. Accordingly, microbial community composition in these sediments can reflect the presence of hydrocarbons, with specific groups being more prolific i... read more 

Organ-Agents: Virtual Human Physiology Simulator via LLMs

arXiv Aug 20, 2025
Recent advances in large language models (LLMs) have enabled new possibilities in simulating complex physiological systems. We introduce Organ-Agents, a multi-agent framework that simulates human physiology via LLM-driven agents. Each Simulator mod... read more 
Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition

Controllable Latent Space Augmentation for Digital Pathology

arXiv Aug 20, 2025
Whole slide image (WSI) analysis in digital pathology presents unique challenges due to the gigapixel resolution of WSIs and the scarcity of dense supervision signals. While Multiple Instance Learning (MIL) is a natural fit for slide-level tasks, t... read more 
Computer Vision and Pattern Recognition

Deep learning approach for screening neonatal cerebral lesions on ultrasound in China.

Nature communications Aug 20, 2025
Timely and accurate diagnosis of severe neonatal cerebral lesions is critical for preventing long-term neurological damage and addressing life-threatening conditions. Cranial ultrasound is the primary screening tool, but the process is time-consuming... read more 
Female Infant, Newborn Humans Brain Male China Ultrasonography Deep Learning Neonatal Screening

Can Artificial Intelligence Doom a Radiologist in Malpractice Cases, and Can This Risk Be Mitigated?

AJR. American journal of roentgenology Aug 20, 2025
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Investigating potential biomarkers associated with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis using Mendelian randomization and transcriptomic analysis.

Arthritis research & therapy Aug 20, 2025
BACKGROUND: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is an autoimmune disorder characterized by multi-organ involvement. Early identification and accurate diagnosis of AAV is crucial for improving prognosis. However, res... read more 
Gene Expression Profiling Transcriptome Humans Gene Regulatory Networks Mendelian Randomization Analysis Biomarkers Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis

Scalable Event-Based Video Streaming for Machines with MoQ

arXiv Aug 20, 2025
Lossy compression and rate-adaptive streaming are a mainstay in traditional video steams. However, a new class of neuromorphic ``event'' sensors records video with asynchronous pixel samples rather than image frames. These sensors are designed for ... read more 
Image and Video Processing Computer Vision and Pattern Recognition Multimedia

Enhanced Predictive Modeling for Hazardous Near-Earth Object Detection: A Comparative Analysis of Advanced Resampling Strategies and Machine Learning Algorithms in Planetary Risk Assessment

arXiv Aug 20, 2025
This study evaluates the performance of several machine learning models for predicting hazardous near-Earth objects (NEOs) through a binary classification framework, including data scaling, power transformation, and cross-validation. Six classifier... read more 
Earth and Planetary Astrophysics Instrumentation and Methods for Astrophysics Artificial Intelligence Machine Learning

On the notion of missingness for path attribution explainability methods in medical settings: Guiding the selection of medically meaningful baselines

arXiv Aug 20, 2025
The explainability of deep learning models remains a significant challenge, particularly in the medical domain where interpretable outputs are critical for clinical trust and transparency. Path attribution methods such as Integrated Gradients rely ... read more 
Machine Learning
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