Artificial Intelligence Medical Compendium

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

Showing 62,731 to 62,740 of 230,507 articles

A Hierarchical Benchmark of Foundation Models for Dermatology

arXiv
Foundation models have transformed medical image analysis by providing robust feature representations that reduce the need for large-scale task-specific training. However, current benchmarks in dermatology often reduce the complex diagnostic taxonomy... read more 

Beyond the Dirac Delta: Mitigating Diversity Collapse in Reinforcement Fine-Tuning for Versatile Image Generation

arXiv
Reinforcement learning (RL) has emerged as a powerful paradigm for fine-tuning large-scale generative models, such as diffusion and flow models, to align with complex human preferences and user-specified tasks. A fundamental limitation remains \texti... read more 

Weaknesses of Facial Emotion Recognition Systems

arXiv
Emotion detection from faces is one of the machine learning problems needed for human-computer interaction. The variety of methods used is enormous, which motivated an in-depth review of articles and scientific studies. Three of the most interesting ... read more 

Explainable Machine Learning for Pediatric Dental Risk Stratification Using Socio-Demographic Determinants

arXiv
Background: Pediatric dental disease remains one of the most prevalent and inequitable chronic health conditions worldwide. Although strong epidemiological evidence links oral health outcomes to socio-economic and demographic determinants, most artif... read more 

HOT-POT: Optimal Transport for Sparse Stereo Matching

arXiv
Stereo vision between images faces a range of challenges, including occlusions, motion, and camera distortions, across applications in autonomous driving, robotics, and face analysis. Due to parameter sensitivity, further complications arise for ster... read more 

Privacy-Preserving Federated Learning with Verifiable Fairness Guarantees

arXiv
Federated learning enables collaborative model training across distributed institutions without centralizing sensitive data; however, ensuring algorithmic fairness across heterogeneous data distributions while preserving privacy remains fundamentally... read more 

Large-scale EM Benchmark for Multi-Organelle Instance Segmentation in the Wild

arXiv
Accurate instance-level segmentation of organelles in electron microscopy (EM) is critical for quantitative analysis of subcellular morphology and inter-organelle interactions. However, current benchmarks, based on small, curated datasets, fail to ca... read more 

NeuralFur: Animal Fur Reconstruction From Multi-View Images

arXiv
Reconstructing realistic animal fur geometry from images is a challenging task due to the fine-scale details, self-occlusion, and view-dependent appearance of fur. In contrast to human hairstyle reconstruction, there are also no datasets that can be ... read more 

Histopath-C: Towards Realistic Domain Shifts for Histopathology Vision-Language Adaptation

arXiv
Medical Vision-language models (VLMs) have shown remarkable performances in various medical imaging domains such as histo\-pathology by leveraging pre-trained, contrastive models that exploit visual and textual information. However, histopathology im... read more 

SDCoNet: Saliency-Driven Multi-Task Collaborative Network for Remote Sensing Object Detection

arXiv
In remote sensing images, complex backgrounds, weak object signals, and small object scales make accurate detection particularly challenging, especially under low-quality imaging conditions. A common strategy is to integrate single-image super-resolu... read more