Artificial Intelligence Medical Compendium

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

Showing 471 to 480 of 213,137 articles

Strong Gravitational Lensing Posterior Sampling in Pixel-Space Using Diffusion Models and Recurrent Inference Machines

arXiv Jul 21, 2026
Modeling galaxy-galaxy strong gravitational lenses to infer the brightness of the source galaxy and the mass distribution of the foreground galaxy is computationally challenging, particularly for high-resolution, high signal-to-noise ratio observatio... read more 
Instrumentation and Methods for Astrophysics astro-ph.CO cs.CV stat.ML

Crowd4D: Scene-Aware Monocular 4D Crowd Reconstruction

arXiv Jul 21, 2026
Recovering scene-consistent 4D crowd motion from monocular video in large-scale scenes remains challenging due to severe depth ambiguity and complex scene geometry. Existing monocular crowd reconstruction methods typically rely on single-plane assump... read more 
Computer Vision and Pattern Recognition

Geospatial Diffusion-based Evolution Synthesis (GeoDES) for Storm-Centered Weather Augmentation

arXiv Jul 21, 2026
While machine learning-based weather models hold significant promise, they struggle to predict the detailed structure of large-scale weather systems such as cyclonic storms. Regional models are constrained by limited historical records within fixed g... read more 
Machine Learning cs.CV

SynPre-FL: Synthetic data-driven pretraining integrated Federated Learning training framework

arXiv Jul 21, 2026
Federated learning (FL) offers a promising approach to privacy-preserving clinical risk prediction, but its deployment remains limited by restricted data sharing, client heterogeneity, class imbalance, and the lack of realistic tabular electronic hea... read more 
Machine Learning cs.AI cs.DC

The C-index illusion: discrimination without calibration in published survival models

arXiv Jul 21, 2026
"Stop Chasing the C-index when Evaluating Survival Analysis Models" (ICML 2026, Spotlight) argued normatively, on synthetic data, that evaluating survival models by discrimination alone, i.e. the concordance index, produces systematically misleading ... read more 
Machine Learning

D3VL: Understanding Driving Scenes from 3D Time Series Data and Video with Language Models

arXiv Jul 21, 2026
Recent advances in Multimodal Large Language Models (MLLMs) have triggered the development of end-to-end MLLMs for autonomous driving. However, the main emphasis to date has been for MLLMs using 2D images and videos. In contrast, this paper considers... read more 
Computer Vision and Pattern Recognition cs.AI

Trustworthy Privacy-Preserving Multimodal Federated Learning for Personalised Breast Cancer Prediction

arXiv Jul 21, 2026
Federated learning has emerged as a potential solution to privacy concerns associated with using sensitive health data for training predictive models, particularly in personalised cancer care. This research investigates whether federated learning can... read more 
Machine Learning cs.AI

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n

arXiv Jul 21, 2026
Incorrect disposal can contaminate campus recycling streams, and a bin-mounted camera could provide feedback as an item is discarded. We evaluated whether synthetic and derived images improve a YOLOv8n detector for this view. The real dataset contain... read more 
Computer Vision and Pattern Recognition

A Deep Learning Framework for Predicting Solar EUV Irradiance During Significant Flares

arXiv Jul 21, 2026
We present FlareEUV, a multimodal deep learning framework for predicting daily extreme ultraviolet (EUV) irradiance at 6.5 nm over three consecutive days during significant solar flares, using multi-instrument observations from NASA's Solar Dynamics ... read more 
Solar and Stellar Astrophysics astro-ph.IM cs.LG

Deep Shape Regression for Planar Curves with Multimodal Covariates

arXiv Jul 21, 2026
The shape of a planar curve is the geometric information that remains once translation, rotation, scale and reparametrisation are removed and is of interest in many health applications, e.g. in neuroimaging. We propose a deep shape regression model f... read more 
Methodology cs.CV cs.LG q-bio.QM stat.ML
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