Artificial Intelligence Medical Compendium

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

Showing 55,411 to 55,420 of 226,647 articles

DIA-CLIP: a universal representation learning framework for zero-shot DIA proteomics

arXiv Feb 2, 2026
Data-independent acquisition mass spectrometry (DIA-MS) has established itself as a cornerstone of proteomic profiling and large-scale systems biology, offering unparalleled depth and reproducibility. Current DIA analysis frameworks, however, require... read more 
Machine Learning cs.AI q-bio.QM

Spatio-Temporal Transformers for Long-Term NDVI Forecasting

arXiv Feb 2, 2026
Long-term satellite image time series (SITS) analysis in heterogeneous landscapes faces significant challenges, particularly in Mediterranean regions where complex spatial patterns, seasonal variations, and multi-decade environmental changes interact... read more 
Computer Vision and Pattern Recognition cs.LG

FlowBypass: Rectified Flow Trajectory Bypass for Training-Free Image Editing

arXiv Feb 2, 2026
Training-free image editing has attracted increasing attention for its efficiency and independence from training data. However, existing approaches predominantly rely on inversion-reconstruction trajectories, which impose an inherent trade-off: longe... read more 
Computer Vision and Pattern Recognition

LDRNet: Large Deformation Registration Model for Chest CT Registration

arXiv Feb 2, 2026
Most of the deep learning based medical image registration algorithms focus on brain image registration tasks.Compared with brain registration, the chest CT registration has larger deformation, more complex background and region over-lap. In this pap... read more 
Computer Vision and Pattern Recognition

Efficient Cross-Country Data Acquisition Strategy for ADAS via Street-View Imagery

arXiv Feb 2, 2026
Deploying ADAS and ADS across countries remains challenging due to differences in legislation, traffic infrastructure, and visual conventions, which introduce domain shifts that degrade perception performance. Traditional cross-country data collectio... read more 
Computer Vision and Pattern Recognition

DOGMA: Weaving Structural Information into Data-centric Single-cell Transcriptomics Analysis

arXiv Feb 2, 2026
Recently, data-centric AI methodology has been a dominant paradigm in single-cell transcriptomics analysis, which treats data representation rather than model complexity as the fundamental bottleneck. In the review of current studies, earlier sequenc... read more 
Machine Learning cs.AI q-bio.GN

WS-IMUBench: Can Weakly Supervised Methods from Audio, Image, and Video Be Adapted for IMU-based Temporal Action Localization?

arXiv Feb 2, 2026
IMU-based Human Activity Recognition (HAR) has enabled a wide range of ubiquitous computing applications, yet its dominant clip classification paradigm cannot capture the rich temporal structure of real-world behaviors. This motivates a shift toward ... read more 
Computer Vision and Pattern Recognition

How Well Do Models Follow Visual Instructions? VIBE: A Systematic Benchmark for Visual Instruction-Driven Image Editing

arXiv Feb 2, 2026
Recent generative models have achieved remarkable progress in image editing. However, existing systems and benchmarks remain largely text-guided. In contrast, human communication is inherently multimodal, where visual instructions such as sketches ef... read more 
Computer Vision and Pattern Recognition

Serum metabolic fingerprinting for diagnosis and therapeutic applications of ovarian endometriosis.

iScience Feb 2, 2026
Ovarian endometriosis (OvE) is a gynecological disorder with endometrial tissue in the ovaries, for which effective non-invasive diagnosis and curative treatments are currently lacking. Serum samples were collected from both discovery and validation ... read more 

Dataset of scattered images using noncoherent light under varying diffusion conditions and projected patterns.

Data in brief Feb 2, 2026
This data article presents an experimental dataset of scattered images, obtained using a low-cost, open-source, Raspberry Pi-based optical system. Each data sample includes two grayscale images of 256 × 256 resolution: the (i) scattered image, and (i... read more 
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