Dermatology

Sézary Syndrome: Survival Trends, Racial Disparities, and Limited Prognostic Value of Routine Registry Variables.

INTRODUCTION: Sézary syndrome (SS) is a rare leukemic cutaneous T-cell lymphoma with limited contemporary population-level outcome data. METHODS: Using SEER-22, we identified 403 adults with first primary SS diagnosed from 2000-2021 and evaluated survival, disparities, and prognostic modeling. RESULTS: Median overall survival (OS) was 48 months; 5-year OS was 42.7%. Survival improved from 39.5 mon...

Serial OCT-based coronary physiology and plaque composition in vessels with nonobstructive coronary lesions following intensive lipid-lowering therapy: YELLOW III sub-study.

BACKGROUND AND AIMS: Non-obstructive coronary plaques are a major source of future coronary events, particularly when characterized by high lipid burden and adverse plaque morphology. While intensive lipid-lowering therapy promotes plaque regression, serial data linking quantitative plaque compositional changes to coronary physiology are limited. We aimed to evaluate the impact of maximal lipid-lo...

Factors to consider in a primary care setting when using convolutional neural network tools for melanoma diagnostics: a retrospective analysis of images and patient characteristics.

Primary care physicians typically perform the initial assessment of skin lesions. Artificial intelligence tools, using techniques such as convolutiona...

MLMarker: a machine learning framework for tissue inference and biomarker discovery.

MLMarker is a machine learning tool that computes continuous tissue similarity scores for proteomics data, addressing the challenge of interpreting co...

Impact on Cost and Expert Time of Data-Efficient Deep Learning for Medical Image Segmentation.

Purpose To develop and systematically evaluate an iterative training approach, termed the expert-guided annotation loop, for efficient reference stand...

FFixR: A Machine Learning Framework for Accurate Somatic Mutation Calling from FFPE RNA-Seq Data in Cancer.

MOTIVATION: Formalin-fixed paraffin-embedded (FFPE) tissues are widely used in clinical and research settings, yet their use for detecting somatic mut...

Performance of multimodal Large Language Models in misdiagnosed dermatologic cases: a pilot study on diagnostic accuracy and human error replication.

BACKGROUND: Multimodal Large Language Models (LLMs) are increasingly positioned as diagnostic assistants in dermatology. However, current research oft...

High-resolution microCT reveals relationships between stomata and interior leaf anatomy in Sorghum.

Stomata are pores in the leaf epidermis that regulate the trade-off between CO2 uptake for photosynthesis and water vapor loss to the atmosphere. Stom...

Molecular characteristics and modifications of glioblastoma affecting the efficacy of immunotherapy.

Glioblastoma is a highly aggressive brain tumor characterized by complex genetic, molecular, and epigenetic features that present significant challeng...

Development and validation of an interpretable machine learning model for early hospital-based differentiation of chikungunya and dengue fever using routine clinical data.

BACKGROUND: Chikungunya fever (CHIKF) and dengue fever are mosquito-borne viral diseases. These infections often circulate in the same regions at the ...

Exploring the Lived Experience of Acne in the United States and the United Kingdom: Social Media Analysis.

BACKGROUND: Acne is a chronic skin condition that primarily affects adolescents and young adults but can persist into adulthood. It can have repercuss...

Three-Dimensional Radiographic and Morphological Features of Ameloblastoma and Odontogenic Keratocyst: A Comparative Cone Beam Computed Tomography Study Using Automatic Segmentation.

OBJECTIVES: We aimed to compare the three-dimensional (3D) radiographic and morphological features, and explore their associations in ameloblastoma (A...

Improved Detection of Lentigo Maligna with AI-Assisted Dermoscopy: A Reader Study in Facial Pigmented Lesions.

BACKGROUND: Differentiating lentigo maligna (LM) from benign facial pigmented lesions remains difficult due to substantial clinical and dermoscopic ov...

Privacy-aware diabetic retinopathy grading and visual lesion-focused interpretability through mixture-of-experts federated deep learning with explainable AI.

Diabetic Retinopathy (DR) is still a major cause of vision loss that can be avoided. This means that we need automated screening systems that can work...

APASA: adaptive selection of informative peritumoral regions for improved automated cancer lesion analysis.

Precise cancer lesion analysis in medical imaging critically depends on the accurate definition of regions of interest (ROIs), which directly influenc...

Adaptive attention and severity estimation framework for robust pearl millet leaf disease identification.

Pearl millet is an important crop in arid regions, but its yield is reduced by foliar diseases like Downy Mildew and Rust. Traditional and deep learni...

Artificial intelligence in pediatric endoscopy for hereditary polyposis syndromes: promises and challenges.

PURPOSE OF REVIEW: Children with hereditary polyposis syndromes require long-term endoscopic surveillance to reduce risks of gastrointestinal complica...

A blood transcriptomic signature anchored to central nervous system pathology enables noninvasive detection of multiple sclerosis.

BACKGROUND: Multiple sclerosis (MS) lacks noninvasive biomarkers anchored to central nervous system (CNS) pathology. This study aimed to identify a bl...

An intelligent MRI-based all-in-one diagnostic strategy for axillary lymph node status in breast cancer.

An integrated diagnostic strategy of preoperative identification of sentinel lymph node (SLN) metastasis, SLN metastatic burden, and non-SLN (NSLN) me...

Evaluating Synthetic Anterior Segment Images for Transferable Eye Disease Recognition.

OBJECTIVE: To evaluate whether prompt-driven synthetic anterior segment disease (ASD) images preserve disease-relevant semantics for transferable ASD ...