Artificial Intelligence Medical Compendium

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

Showing 46,291 to 46,300 of 224,055 articles

DLEBench: Evaluating Small-scale Object Editing Ability for Instruction-based Image Editing Model

arXiv
Significant progress has been made in the field of Instruction-based Image Editing Models (IIEMs). However, while these models demonstrate plausible adherence to instructions and strong reasoning ability on current benchmarks, their ability to edit s... read more 

ReDON: Recurrent Diffractive Optical Neural Processor with Reconfigurable Self-Modulated Nonlinearity

arXiv
Diffractive optical neural networks (DONNs) have demonstrated unparalleled energy efficiency and parallelism by processing information directly in the optical domain. However, their computational expressivity is constrained by static, passive diffrac... read more 

Annotation-Free Visual Reasoning for High-Resolution Large Multimodal Models via Reinforcement Learning

arXiv
Current Large Multimodal Models (LMMs) struggle with high-resolution visual inputs during the reasoning process, as the number of image tokens increases quadratically with resolution, introducing substantial redundancy and irrelevant information. A c... read more 

When Does Multimodal Learning Help in Healthcare? A Benchmark on EHR and Chest X-Ray Fusion

arXiv
Machine learning holds promise for advancing clinical decision support, yet it remains unclear when multimodal learning truly helps in practice, particularly under modality missingness and fairness constraints. In this work, we conduct a systematic b... read more 

Incremental dimension reduction for efficient and accurate visual anomaly detection

arXiv
While nowadays visual anomaly detection algorithms use deep neural networks to extract salient features from images, the high dimensionality of extracted features makes it difficult to apply those algorithms to large data with 1000s of images. To add... read more 

Pseudo Contrastive Learning for Diagram Comprehension in Multimodal Models

arXiv
Recent multimodal models such as Contrastive Language-Image Pre-training (CLIP) have shown remarkable ability to align visual and linguistic representations. However, domains where small visual differences carry large semantic significance, such as d... read more 

Hyperdimensional Cross-Modal Alignment of Frozen Language and Image Models for Efficient Image Captioning

arXiv
Large unimodal foundation models for vision and language encode rich semantic structures, yet aligning them typically requires computationally intensive multimodal fine-tuning. Such approaches depend on large-scale parameter updates, are resource int... read more 

CycleBEV: Regularizing View Transformation Networks via View Cycle Consistency for Bird's-Eye-View Semantic Segmentation

arXiv
Transforming image features from perspective view (PV) space to bird's-eye-view (BEV) space remains challenging in autonomous driving due to depth ambiguity and occlusion. Although several view transformation (VT) paradigms have been proposed, the ch... read more 

No Calibration, No Depth, No Problem: Cross-Sensor View Synthesis with 3D Consistency

arXiv
We present the first study of cross-sensor view synthesis across different modalities. We examine a practical, fundamental, yet widely overlooked problem: getting aligned RGB-X data, where most RGB-X prior work assumes such pairs exist and focuses on... read more 

Evaluating large language model responses to patient questions on ulnar collateral ligament repair.

Clinics in shoulder and elbow
BACKGROUND: The incidence of ulnar collateral ligament (UCL) repair continues to increase, so evaluating the accuracy and readability of information about this procedure that is produced by artificial intelligence (AI) models is important. This study... read more