Artificial Intelligence Medical Compendium

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

Showing 42,191 to 42,200 of 223,853 articles

FDeID-Toolbox: Face De-Identification Toolbox

arXiv
Face de-identification (FDeID) aims to remove personally identifiable information from facial images while preserving task-relevant utility attributes such as age, gender, and expression. It is critical for privacy-preserving computer vision, yet the... read more 

DiT-IC: Aligned Diffusion Transformer for Efficient Image Compression

arXiv
Diffusion-based image compression has recently shown outstanding perceptual fidelity, yet its practicality is hindered by prohibitive sampling overhead and high memory usage. Most existing diffusion codecs employ U-Net architectures, where hierarchic... read more 

Towards Faithful Multimodal Concept Bottleneck Models

arXiv
Concept Bottleneck Models (CBMs) are interpretable models that route predictions through a layer of human-interpretable concepts. While widely studied in vision and, more recently, in NLP, CBMs remain largely unexplored in multimodal settings. For th... read more 

Diffusion-Based Feature Denoising and Using NNMF for Robust Brain Tumor Classification

arXiv
Brain tumor classification from magnetic resonance imaging, which is also known as MRI, plays a sensitive role in computer-assisted diagnosis systems. In recent years, deep learning models have achieved high classification accuracy. However, their se... read more 

Towards Spatio-Temporal World Scene Graph Generation from Monocular Videos

arXiv
Spatio-temporal scene graphs provide a principled representation for modeling evolving object interactions, yet existing methods remain fundamentally frame-centric: they reason only about currently visible objects, discard entities upon occlusion, an... read more 

Visual-ERM: Reward Modeling for Visual Equivalence

arXiv
Vision-to-code tasks require models to reconstruct structured visual inputs, such as charts, tables, and SVGs, into executable or structured representations with high visual fidelity. While recent Large Vision Language Models (LVLMs) achieve strong r... read more 

Prediction of favorable outcomes of acute basilar artery occlusion using machine learning.

Journal of neurointerventional surgery
BACKGROUND: This study aims to develop an interpretable machine learning model using SHapley Additive exPlanations (SHAP) to predict favorable outcomes based on clinical, imaging, and angiographic data. METHODS: This study analyzed data from 184 pati... read more 

Predicting infarct outcomes after extended time window thrombectomy in large vessel occlusion using knowledge guided deep learning.

Journal of neurointerventional surgery
BACKGROUND: Predicting the final infarct after an extended time window mechanical thrombectomy (MT) is beneficial for treatment planning in acute ischemic stroke (AIS). By introducing guidance from prior knowledge, this study aims to improve the accu... read more 

Facilitating genome annotation using ANNEXA and long-read RNA sequencing

bioRxiv
With the advent of complete genome assemblies, genome annotation has become essential for the functional interpretation of genomic data. Long-read RNA sequencing (LR-RNAseq) technologies have significantly improved transcriptome annotation by enablin... read more 

Generative AI-based design of hybrid transcriptional activator proteins with new DNA-binding specificity

bioRxiv
Transcriptional control arises from the specific recognition of promoter DNA by transcription factors (TFs), forming the basis of cellular information processing and gene regulation. In synthetic biology, TF-promoter interactions are assembled into g... read more