Artificial Intelligence Medical Compendium

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

Showing 20,781 to 20,790 of 216,088 articles

BenchCAD: A Comprehensive, Industry-Standard Benchmark for Programmatic CAD

arXiv
Industrial Computer-Aided Design (CAD) code generation requires models to produce executable parametric programs from visual or textual inputs. Beyond recognizing the outer shape of a part, this task involves understanding its 3D structure, inferring... read more 

BEACON: A Multimodal Dataset for Learning Behavioral Fingerprints from Gameplay Data

arXiv
Continuous authentication in high-stakes digital environments requires datasets with fine-grained behavioral signals under realistic cognitive and motor demands. But current benchmarks are often limited by small scale, unimodal sensing or lack of syn... read more 

Attractor-Vascular Coupling Theory: Formal Grounding and Empirical Validation for AAMI-Standard Cuffless Blood Pressure Estimation from Smartphone Photoplethysmography

arXiv
This work proposes Attractor-Vascular Coupling Theory (AVCT), a mathematical framework showing that cardiac attractor geometry encodes blood pressure (BP) information sufficient for AAMI-standard estimation, and validates the theory through a calibra... read more 

CADBench: A Multimodal Benchmark for AI-Assisted CAD Program Generation

arXiv
Recovering editable CAD programs from images or 3D observations is central to AI-assisted design, but progress is difficult to measure because existing evaluations are fragmented across datasets, modalities, and metrics. We introduce CADBench, a unif... read more 

AssayBench: An Assay-Level Virtual Cell Benchmark for LLMs and Agents

arXiv
Recent advances in machine learning and large-scale biological data collections have revived the prospect of building a virtual cell, a computational model of cellular behavior that could accelerate biological discovery. One of the most compelling pr... read more 

Geometry-aware Prototype Learning for Cross-domain Few-shot Medical Image Segmentation

arXiv
Cross-domain few-shot medical image segmentation (CD-FSMIS) requires a model to generalise simultaneously to novel anatomical categories and unseen imaging domains from only a handful of annotated examples. Existing prototypical approaches inevitably... read more 

Count Anything at Any Granularity

arXiv
Open-world object counting remains brittle: despite rapid advances in vision-language models (VLMs), reliably counting the objects a user intends is far from solved. We argue that a central reason is that counting granularity is left implicit; users ... read more 

Counterfactual Stress Testing for Image Classification Models

arXiv
Deep learning models in medical imaging often fail when deployed in new clinical environments due to distribution shifts in demographics, scanner hardware, or acquisition protocols. A central challenge is underspecification, where models with similar... read more 

Confidence-Guided Diffusion Augmentation for Enhanced Bangla Compound Character Recognition

arXiv
Recognition of handwritten Bangla compound characters remains a challenging problem due to complex character structures, large intra-class variation, and limited availability of high-quality annotated data. Existing Bangla handwritten character recog... read more 

Pixal3D: Pixel-Aligned 3D Generation from Images

arXiv
Recent advances in 3D generative models have rapidly improved image-to-3D synthesis quality, enabling higher-resolution geometry and more realistic appearance. Yet fidelity, which measures pixel-level faithfulness of the generated 3D asset to the inp... read more