Artificial Intelligence Medical Compendium

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

Showing 50,861 to 50,870 of 225,062 articles

WISE: A Multimodal Search Engine for Visual Scenes, Audio, Objects, Faces, Speech, and Metadata

arXiv
In this paper, we present WISE, an open-source audiovisual search engine which integrates a range of multimodal retrieval capabilities into a single, practical tool accessible to users without machine learning expertise. WISE supports natural-languag... read more 

3DLAND: 3D Lesion Abdominal Anomaly Localization Dataset

arXiv
Existing medical imaging datasets for abdominal CT often lack three-dimensional annotations, multi-organ coverage, or precise lesion-to-organ associations, hindering robust representation learning and clinical applications. To address this gap, we in... read more 

GRAIL: Geometry-Aware Retrieval-Augmented Inference with LLMs over Hyperbolic Representations of Patient Trajectories

arXiv
Predicting future clinical events from longitudinal electronic health records (EHRs) is challenging due to sparse multi-type clinical events, hierarchical medical vocabularies, and the tendency of large language models (LLMs) to hallucinate when reas... read more 

TRACE: Temporal Reasoning via Agentic Context Evolution for Streaming Electronic Health Records (EHRs)

arXiv
Large Language Models (LLMs) encode extensive medical knowledge but struggle to apply it reliably to longitudinal patient trajectories, where evolving clinical states, irregular timing, and heterogeneous events degrade performance over time. Existing... read more 

Thinking Like a Radiologist: A Dataset for Anatomy-Guided Interleaved Vision Language Reasoning in Chest X-ray Interpretation

arXiv
Radiological diagnosis is a perceptual process in which careful visual inspection and language reasoning are repeatedly interleaved. Most medical large vision language models (LVLMs) perform visual inspection only once and then rely on text-only chai... read more 

Amortized Reasoning Tree Search: Decoupling Proposal and Decision in Large Language Models

arXiv
Reinforcement Learning with Verifiable Rewards (RLVR) has established itself as the dominant paradigm for instilling rigorous reasoning capabilities in Large Language Models. While effective at amplifying dominant behaviors, we identify a critical pa... read more 

RoadscapesQA: A Multitask, Multimodal Dataset for Visual Question Answering on Indian Roads

arXiv
Understanding road scenes is essential for autonomous driving, as it enables systems to interpret visual surroundings to aid in effective decision-making. We present Roadscapes, a multitask multimodal dataset consisting of upto 9,000 images captured ... read more 

Dual-Phase Cross-Modal Contrastive Learning for CMR-Guided ECG Representations for Cardiovascular Disease Assessment

arXiv
Cardiac magnetic resonance imaging (CMR) offers detailed evaluation of cardiac structure and function, but its limited accessibility restricts use to selected patient populations. In contrast, the electrocardiogram (ECG) is ubiquitous and inexpensive... read more 

RADAR: Revealing Asymmetric Development of Abilities in MLLM Pre-training

arXiv
Pre-trained Multi-modal Large Language Models (MLLMs) provide a knowledge-rich foundation for post-training by leveraging their inherent perception and reasoning capabilities to solve complex tasks. However, the lack of an efficient evaluation framew... read more 

Robustness of Object Detection of Autonomous Vehicles in Adverse Weather Conditions

arXiv
As self-driving technology advances toward widespread adoption, determining safe operational thresholds across varying environmental conditions becomes critical for public safety. This paper proposes a method for evaluating the robustness of object d... read more