Artificial Intelligence Medical Compendium

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

Showing 19,871 to 19,880 of 215,899 articles

Simulating the spectrum, not the syndrome: Large scale individualized modeling of oral reading in stroke aphasia

bioRxiv
Computational models are a linchpin in our understanding of the neurocognitive basis of reading. These models can simulate idealized profiles of alexia syndromes, but in reality, individuals with alexia present with a wide range of mixed deficits rat... read more 

Deep Representation Learning on Whole-Brain Population Dynamics Uncovers Geometrically Separable Neural Codes

bioRxiv
Learning interpretable low-dimensional representations of whole-brain neuronal dynamics remains a major computational challenge in systems neuroscience. We present a wiring-agnostic deep-learning framework that couples a convolutional encoder with a ... read more 

Machine learning-based prediction of memory requirements for metagenomic assembly in high-performance computing environments

bioRxiv
Metagenomic assembly can be a computationally intensive step in microbiome analysis, with memory requirements that vary widely depending on input data characteristics. In workflow systems like Galaxy and large-scale platforms like MGnify, which run t... read more 

Morphological fingerprints enable machine learning based inference of neuroblastoma cell states without transcriptomics

bioRxiv
Inference of cancer cell states is essential for understanding oncogenic mechanisms and predicting clinical outcomes, yet current reliance on transcriptomic profiling limits scalability and real-time monitoring. Here, we show that cell morphology pro... read more 

Molecular Methods to Detect Vibrio cholerae and Associated Bacteriophages among Diarrheal Patients in Bangladesh

medRxiv
Molecular diagnostics to detect Vibrio cholerae (Vc) may be negatively impacted by pathogen-specific lytic bacteriophage (phage) predation. To address this problem, phage detection as a proxy for pathogen detection has been proposed. However, efforts... read more 

Retrieval-Augmented Claude Opus 4.7 and GPT-5.5 Surpass Human Performance on the Nuclear Cardiology Board Preparation Exam (and Claude Drafts a Paper About it)

medRxiv
Background - Previous studies evaluated large language model (LLM) performance on the American Society of Nuclear Cardiology (ASNC) Board Preparation Exam. Without domain-specific context, the best model (GPT-4o) achieved 63.1%, below the estimated 6... read more 

Contactless ultrasound chest vibration mapping discriminates respiratory and cardiac patients from healthy individuals.

medRxiv
Contactless assessment of cardiopulmonary function remains an unmet need, with current approaches relying either on subjective clinical examination or on resource intensive imaging. We evaluated a novel multipoint airborne ultrasound surface motion c... read more 

Estimation of Physiological Metrics from Resting ECGs Using Deep Learning in the UK Biobank, Including submaximal exercise derived VO2max, Body Fat Percentage, and Grip Strength

medRxiv
Maximal oxygen consumption VO2max is the gold standard for cardiorespiratory fitness but requires resource-intensive physical testing. Recent reports show that machine learning models can extract additional information from ECGs, yet the potential of... read more 

Benchmarking foundation models for improving confounding control in target trial emulation

medRxiv
Machine learning models for causal inference aim to adjust for confounding factors that are associated with both an exposure and an outcome, creating a spurious biased association. But, these methods are rarely empirically evaluated to assess their s... read more 

Prediction of Pivot Shift Grade Using In-Vivo Ultrasound Bone Tracking During Sit-Stand-Sit: A Machine Learning Feasibility Study

medRxiv
Background: The pivot shift (PS) test is the most specific clinical examination for anterolateral rotational instability in ACL deficient knees, yet grading remains subjective, as evidenced by poor interobserver reliability, particularly for Grade 2.... read more