Artificial Intelligence Medical Compendium

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

Showing 62,741 to 62,750 of 230,507 articles

Fine-Tuning Cycle-GAN for Domain Adaptation of MRI Images

arXiv Jan 18, 2026
Magnetic Resonance Imaging (MRI) scans acquired from different scanners or institutions often suffer from domain shifts owing to variations in hardware, protocols, and acquisition parameters. This discrepancy degrades the performance of deep learning... read more 
Computer Vision and Pattern Recognition

XRefine: Attention-Guided Keypoint Match Refinement

arXiv Jan 18, 2026
Sparse keypoint matching is crucial for 3D vision tasks, yet current keypoint detectors often produce spatially inaccurate matches. Existing refinement methods mitigate this issue through alignment of matched keypoint locations, but they are typicall... read more 
Computer Vision and Pattern Recognition

BirdsEye-RU: A Dataset For Detecting Faces from Overhead Images

arXiv Jan 18, 2026
Detecting faces in overhead images remains a significant challenge due to extreme scale variations and environmental clutter. To address this, we created the BirdsEye-RU dataset, a comprehensive collection of 2,978 images containing over eight thousa... read more 
Computer Vision and Pattern Recognition

Press Start to Charge: Videogaming the Online Centralized Charging Scheduling Problem

arXiv Jan 18, 2026
We study the online centralized charging scheduling problem (OCCSP). In this problem, a central authority must decide, in real time, when to charge dynamically arriving electric vehicles (EVs), subject to capacity limits, with the objective of balanc... read more 
Machine Learning

PISE: Physics-Anchored Semantically-Enhanced Deep Computational Ghost Imaging for Robust Low-Bandwidth Machine Perception

arXiv Jan 18, 2026
We propose PISE, a physics-informed deep ghost imaging framework for low-bandwidth edge perception. By combining adjoint operator initialization with semantic guidance, PISE improves classification accuracy by 2.57% and reduces variance by 9x at 5% s... read more 
Computer Vision and Pattern Recognition eess.IV

Artificial Intelligence in Materials Science and Engineering: Current Landscape, Key Challenges, and Future Trajectorie

arXiv Jan 18, 2026
Artificial Intelligence is rapidly transforming materials science and engineering, offering powerful tools to navigate complexity, accelerate discovery, and optimize material design in ways previously unattainable. Driven by the accelerating pace of ... read more 
Materials Science cs.AI physics.comp-ph quant-ph

Life, Machine Learning, and the Search for Habitability: Predicting Biosignature Fluxes for the Habitable Worlds Observatory

arXiv Jan 18, 2026
Future direct-imaging flagship missions, such as NASA's Habitable Worlds Observatory (HWO), face critical decisions in prioritizing observations due to extremely stringent time and resource constraints. In this paper, we introduce two advanced machin... read more 
Machine Learning cs.AI cs.CV

HERMES: A Unified Open-Source Framework for Realtime Multimodal Physiological Sensing, Edge AI, and Intervention in Closed-Loop Smart Healthcare Applications

arXiv Jan 18, 2026
Intelligent assistive technologies are increasingly recognized as critical daily-use enablers for people with disabilities and age-related functional decline. Longitudinal studies, curation of quality datasets, live monitoring in activities of daily ... read more 
Systems and Control cs.LG

Adversarial Drift-Aware Predictive Transfer: Toward Durable Clinical AI

arXiv Jan 17, 2026
Clinical AI systems frequently suffer performance decay post-deployment due to temporal data shifts, such as evolving populations, diagnostic coding updates (e.g., ICD-9 to ICD-10), and systemic shocks like the COVID-19 pandemic. Addressing this ``ag... read more 
Applications cs.LG stat.ME

Accelerated MR Elastography Using Learned Neural Network Representation

arXiv Jan 17, 2026
To develop a deep-learning method for achieving fast high-resolution MR elastography from highly undersampled data without the need of high-quality training dataset. We first framed the deep neural network representation as a nonlinear extension of t... read more 
Signal Processing cs.CV cs.LG q-bio.QM
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