Dermatology

Focus-to-Perceive Representation Learning: A Cognition-Inspired Hierarchical Framework for Endoscopic Video Analysis

Endoscopic video analysis is essential for early gastrointestinal screening but remains hindered by limited high-quality annotations. While self-supervised video pre-training shows promise, existing methods developed for natural videos prioritize dense spatio-temporal modeling and exhibit motion bias, overlooking the static, structured semantics critical to clinical decision-making. To address thi...

Adapting Segment Anything Model 3 for Concept-Driven Lesion Segmentation in Medical Images: An Experimental Study

Accurate lesion segmentation is essential in medical image analysis, yet most existing methods are designed for specific anatomical sites or imaging modalities, limiting their generalizability. Recent vision-language foundation models enable concept-driven segmentation in natural images, offering a promising direction for more flexible medical image analysis. However, concept-prompt-based lesion s...

Self-supervised learning for a gene program-centric view of cell states

Single-cell omics has extended the biological interrogation of cell state from examining the expression of individual genes to unbiased profiling of t...

An Image Dataset of Common Skin Diseases of Bangladesh and Benchmarking Performance with Machine Learning Models

Skin diseases are a major public health concern worldwide, and their detection is often challenging without access to dermatological expertise. In cou...

Colon-Bench: An Agentic Workflow for Scalable Dense Lesion Annotation in Full-Procedure Colonoscopy Videos

Early screening via colonoscopy is critical for colon cancer prevention, yet developing robust AI systems for this domain is hindered by the lack of d...

PGR-Net: Prior-Guided ROI Reasoning Network for Brain Tumor MRI Segmentation

Brain tumor MRI segmentation is essential for clinical diagnosis and treatment planning, enabling accurate lesion detection and radiotherapy target de...

SkinCLIP-VL: Consistency-Aware Vision-Language Learning for Multimodal Skin Cancer Diagnosis

The deployment of vision-language models (VLMs) in dermatology is hindered by the trilemma of high computational costs, extreme data scarcity, and the...

ODySSeI: An Open-Source End-to-End Framework for Automated Detection, Segmentation, and Severity Estimation of Lesions in Invasive Coronary Angiography Images

Invasive Coronary Angiography (ICA) is the clinical gold standard for the assessment of coronary artery disease. However, its interpretation remains s...

Coupled Solvent and Protein Dynamics Confer Differences in Exon-19 Deletion Mutants of the Epidermal Growth Factor Receptor Kinase

Deletions in Exon-19 of the epidermal growth factor receptor (EGFR) play a pivotal role in the pathogenesis of non-small cell lung cancer (NSCLC), inf...

Comparative Evaluation of Microstructural Diffusion Methods in Characterizing Multiple Sclerosis Lesions: The Importance of multi-b shells acquisition

Background: Diffusion MRI (dMRI) is widely used to assess microstructural abnormalities in multiple sclerosis (MS), yet conventional diffusion tensor ...

DermaFlux: Synthetic Skin Lesion Generation with Rectified Flows for Enhanced Image Classification

Despite recent advances in deep generative modeling, skin lesion classification systems remain constrained by the limited availability of large, diver...

Unmasking Biases and Reliability Concerns in Convolutional Neural Networks Analysis of Cancer Pathology Images

Convolutional Neural Networks have shown promising effectiveness in identifying different types of cancer from radiographs. However, the opaque nature...

Rational Design of Selective IL-2-based Activators for CAR T Cells Using AlphaFold3 and Physics-Informed Machine Learning

Recombinant human Interleukin-2 (rhIL-2, Aldesleukin) is used in immunotherapy for metastatic melanoma and renal cell carcinoma. Low-dose IL-2 has bee...

Predicting targeted- and immunotherapeutic response outcomes in melanoma with single-cell Raman Spectroscopy and AI

Identifying predictive biomarkers of immunotherapeutic response in melanoma remains an outstanding challenge. Existing transcriptomic and proteomic pr...

Cross-Attention Enables Context-Aware Multimodal Skin Lesion Diagnosis

Clinical diagnosis of skin lesions integrates visual dermoscopic features with patient context such as age, skin type, and lesion characteristics. How...

UltrasoundAgents: Hierarchical Multi-Agent Evidence-Chain Reasoning for Breast Ultrasound Diagnosis

Breast ultrasound diagnosis typically proceeds from global lesion localization to local sign assessment and then evidence integration to assign a BI-R...

Conversational Artificial Intelligence-Enabled Molecular Characterization of Sezary Syndrome Reveals Distinct Pathway-Level Alterations Compared with Non-Sezary Cutaneous T-Cell Lymphoma

ABSTRACT Background: Sezary syndrome (SS) represents an aggressive leukemic variant of cutaneous T-cell lymphoma (CTCL) with distinct clinical behavio...

Diagnosis of Multiple Sclerosis Using Multimodal Deep Learning Integrating Lesion and Normal-Appearing White Matter: A Retrospective Study with International Multicentre External Validation

Background: Current diagnostic criteria for multiple sclerosis (MS) rely on white matter lesions (WMLs), which are not specific and often occur in oth...

Experimental multi-center validation of a radiomics-based photonic quantum precision medicine architecture for lesion-level prediction of anti-PD-1 response in non-small cell lung cancer

Background: Previous research has shown that radiomics-based machine learning models are promising precision medicine tools for lesion-level predictio...

Composed Vision-Language Retrieval for Skin Cancer Case Search via Joint Alignment of Global and Local Representations

Medical image retrieval aims to identify clinically relevant lesion cases to support diagnostic decision making, education, and quality control. In pr...