Artificial Intelligence Medical Compendium

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

Showing 24,801 to 24,810 of 217,472 articles

Entropy-Dominated Temporal Vocal Dynamics as Digital Biomarkers for Depression Detection

arXiv Apr 29, 2026
Automated depression detection often relies on static aggregation of conversational signals, potentially obscuring clinically meaningful behavioral dynamics. We investigated whether entropy-driven temporal biomarkers improve depression detection beyo... read more 
Other Quantitative Biology cs.AI cs.LG

Fidelity, Diversity, and Privacy: A Multi-Dimensional LLM Evaluation for Clinical Data Augmentation

arXiv Apr 29, 2026
The scarcity of high-quality annotated medical data, particularly in mental health, poses a significant bottleneck for training robust machine learning models. Privacy regulations restrict data sharing, making synthetic data generation a promising al... read more 
Machine Learning cs.CR

Validating the Clinical Utility of CineECG 3D Reconstructions through Cross-Modal Feature Attribution

arXiv Apr 29, 2026
Deep learning models for 12-lead electrocardiogram (ECG) analysis achieve high diagnostic performance but lack the intuitive interpretability required for clinical integration. Standard feature attribution methods are limited by the inherent difficul... read more 
Image and Video Processing cs.LG stat.ML

Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods

arXiv Apr 29, 2026
Deep learning for cross-subject EEG decoding is hindered by high inter-subject variability, which introduces a severe domain shift between training and unseen test subjects. This survey presents a comprehensive review of deep learning methodologies s... read more 
Machine Learning eess.SP

Detecting Clinical Discrepancies in Health Coaching Agents: A Dual-Stream Memory and Reconciliation Architecture

arXiv Apr 29, 2026
As Large Language Model (LLM) agents transition from single-session tools to persistent systems managing longitudinal healthcare journeys, their memory architectures face a critical challenge: reconciling two imperfect sources of truth. The patient's... read more 
Machine Learning cs.AI cs.CL

Co-Evolving Policy Distillation

arXiv Apr 29, 2026
RLVR and OPD have become standard paradigms for post-training. We provide a unified analysis of these two paradigms in consolidating multiple expert capabilities into a single model, identifying capability loss in different ways: mixed RLVR suffers f... read more 
Machine Learning

Reconstruction by Generation: 3D Multi-Object Scene Reconstruction from Sparse Observations

arXiv Apr 29, 2026
Accurately reconstructing complex full multi-object scenes from sparse observations remains a core challenge in computer vision and a key step toward scalable and reliable simulation for robotics. In this work, we introduce RecGen, a generative frame... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG cs.RO

InterPartAbility: Text-Guided Part Matching for Interpretable Person Re-Identification

arXiv Apr 29, 2026
Text-to-image person re-identification (TI-ReID) relies on natural-language text description to retrieve top matching individuals from a large gallery of images. While recent large vision-language models (VLMs) achieve strong retrieval performance, t... read more 
Computer Vision and Pattern Recognition

How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance

arXiv Apr 29, 2026
In generative modeling, we often wish to produce samples that maximize a user-specified reward such as aesthetic quality or alignment with human preferences, a problem known as guidance. Despite their widespread use, existing guidance methods either ... read more 
Machine Learning cs.AI

Evaluating TabPFN for Mild Cognitive Impairment to Alzheimer's Disease Conversion in Data Limited Settings

arXiv Apr 29, 2026
Accurate prediction of conversion from Mild Cognitive Impairment (MCI) to Alzheimers Diseases (AD) is essential for early intervention, however, developing reliable conversion predictive models is difficult to develop due to limited longitudinal data... read more 
Artificial Intelligence
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