Artificial Intelligence Medical Compendium

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

Showing 58,531 to 58,540 of 227,634 articles

Benchmarking Deep Learning-Based Reconstruction Methods for Photoacoustic Computed Tomography with Clinically Relevant Synthetic Datasets

arXiv
Deep learning (DL)-based image reconstruction methods for photoacoustic computed tomography (PACT) have developed rapidly in recent years. However, most existing methods have not employed standardized datasets, and their evaluations rely on tradition... read more 

Conservative & Aggressive NaNs Accelerate U-Nets for Neuroimaging

arXiv
Deep learning models for neuroimaging increasingly rely on large architectures, making efficiency a persistent concern despite advances in hardware. Through an analysis of numerical uncertainty of convolutional neural networks (CNNs), we observe that... read more 

Federated Proximal Optimization for Privacy-Preserving Heart Disease Prediction: A Controlled Simulation Study on Non-IID Clinical Data

arXiv
Healthcare institutions have access to valuable patient data that could be of great help in the development of improved diagnostic models, but privacy regulations like HIPAA and GDPR prevent hospitals from directly sharing data with one another. Fede... read more 

FASTR: Reimagining FASTQ via Compact Image-inspired Representation

arXiv
Motivation: High-throughput sequencing (HTS) enables population-scale genomics but generates massive datasets, creating bottlenecks in storage, transfer, and analysis. FASTQ, the standard format for over two decades, stores one byte per base and one ... read more 

Rethinking Benchmarks for Differentially Private Image Classification

arXiv
We revisit benchmarks for differentially private image classification. We suggest a comprehensive set of benchmarks, allowing researchers to evaluate techniques for differentially private machine learning in a variety of settings, including with and ... read more 

PUNCH: Physics-informed Uncertainty-aware Network for Coronary Hemodynamics

arXiv
Coronary microvascular dysfunction (CMD) affects millions worldwide yet remains underdiagnosed because gold-standard physiological measurements are invasive and variably reproducible. We introduce a non-invasive, uncertainty-aware framework for estim... read more 

Reasoning Beyond Literal: Cross-style Multimodal Reasoning for Figurative Language Understanding

arXiv
Vision-language models (VLMs) have demonstrated strong reasoning abilities in literal multimodal tasks such as visual mathematics and science question answering. However, figurative language, such as sarcasm, humor, and metaphor, remains a significan... read more 

NewPINNs: Physics-Informing Neural Networks Using Conventional Solvers for Partial Differential Equations

arXiv
We introduce NewPINNs, a physics-informing learning framework that couples neural networks with conventional numerical solvers for solving differential equations. Rather than enforcing governing equations and boundary conditions through residual-base... read more 

Structural Complexity of Brain MRI reveals age-associated patterns

arXiv
We adapt structural complexity analysis to three-dimensional signals, with an emphasis on brain magnetic resonance imaging (MRI). This framework captures the multiscale organization of volumetric data by coarse-graining the signal at progressively la... read more 

Semi-Supervised Domain Adaptation with Latent Diffusion for Pathology Image Classification

arXiv
Deep learning models in computational pathology often fail to generalize across cohorts and institutions due to domain shift. Existing approaches either fail to leverage unlabeled data from the target domain or rely on image-to-image translation, whi... read more