Dermatology

Software-based de-filtering restores quantitative accuracy in Clarity2D-enhanced whole-body bone scintigraphy.

OBJECTIVE: To determine whether software-based de-filtering can restore the quantitative accuracy of the bone scan index (BSI) and the number of hot spots (HSn) in whole-body scintigraphy images degraded by the Clarity2D noise-reduction filter. METHODS: In this IRB-approved retrospective study, 101 adults (mean age ± SD: 67 ± 13 years) who underwent 99mTc-HMDP whole-body scintigraphy on a cadmium-...

Dermoscopy-guided high-frequency ultrasound: Principles and applications in dermatology.

Conventional skin imaging modalities are often bulky, expensive, and impractical for routine dermatology practice. There is a need for a portable, multimodal imaging tool that integrates high-resolution surface and subsurface visualization at the point of care. The aim of this study was to describe the design, technical capabilities, and clinical application of dermoscopy-guided high-frequency ult...

Spatial radiomics-based interpretable multimodal machine learning model enhances outcomes prediction for minor stroke: A multicenter cohort study.

INTRODUCTION: Accurately identifying unfavorable outcomes is crucial for the clinical management of minor stroke. Conventional imaging prediction mode...

A novel polypeptide molecule attenuates atopic dermatitis by targeting CCR8-CCL1 axis.

Atopic dermatitis (AD) is a common chronic inflammatory skin disease with diverse clinical phenotypes. Although a variety of drugs are available, the ...

Augmented intelligence for multimodal virtual biopsy in breast cancer using generative artificial intelligence.

OBJECTIVE: This study aims to propose a multimodal, multi-view deep learning approach for breast cancer virtual biopsy, a non-invasive classification ...

Fully automated quantification of net water uptake in acute ischemic stroke using only non-contrast CT imaging.

OBJECTIVE: Estimating early lesion progression in ischemic stroke is essential for assessing thrombolytic treatment efficacy. While computed tomograph...

Utilizing data mining to improve asthma control in children: a study on influential factors.

OBJECTIVE: To identify the most influential features of asthma control in children and to assess whether feature selection improves model performance....

Risk Prediction for Delayed Bleeding After Endoscopic Submucosal Dissection in Colorectal Precancerous Lesions Using Artificial Intelligence: Retrospective Clinical Trial.

BACKGROUND: Delayed bleeding is a common complication after endoscopic submucosal dissection. OBJECTIVE: Our study aimed to assess risk factors for de...

GloW-VSNet: A scribble-based weakly supervised framework for global-view vitiligo lesion segmentation.

Vitiligo lesion identification is essential for quantifying disease severity, monitoring disease progression and assessing treatment response, particu...

Artificial Intelligence in Acne Diagnosis and Management: Current Applications and Future Directions.

Interobserver variability in histopathologic diagnosis of melanocytic neoplasms.

BACKGROUND: Precise histopathologic diagnosis of melanocytic neoplasms is required to guide appropriate clinical management; however, significant inte...

ReticularNet: Automated Pixel-Level Segmentation of Reticular Pseudodrusen on Near-Infrared Reflectance Images by Deep Learning.

OBJECTIVE: Reticular pseudodrusen (RPD) represent an important biomarker in age-related macular degeneration (AMD) but are difficult to grade and ofte...

Exploring shared diagnostic genes and molecular mechanisms in multiple sclerosis and psoriasis through bioinformatics analysis and machine learning.

BACKGROUND: Multiple sclerosis (MS) and psoriasis are both immune-mediated inflammatory diseases. Previous studies have reported comorbidity between M...

Modulating tumor mechanics and vascular barriers to enhance chemotherapy efficacy in pancreatic tumors and melanoma.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense stroma and dysfunctional vasculature, limiting drug delivery and immune infiltrati...

Interpreting Deep Learning-Based Prediction of the BRAF V600E Mutation Using Diagnostic Whole Slide Images in Skin Cutaneous Melanoma.

Deep learning (DL) models have shown promise in predicting molecular alterations directly from hematoxylin and eosin-stained whole slide images in a v...

Revolutionizing Liver Imaging: Artificial Intelligence-Driven Advances in Diagnostics and Staging.

Artificial intelligence (AI) has emerged as a transformative tool in liver imaging, offering enhanced diagnostic accuracy, efficiency, and reproducibi...

Super-resolution deep learning reconstruction improves brain MRI quality and detection of metastases.

PURPOSE: Accurate identification of brain metastases is critical for determining prognosis and guiding treatment. Deep learning reconstruction (DLR) e...

CoREST complex inhibition alters RNA splicing to promote neoantigen expression and enhance tumor immunity.

Epigenetic macromolecular enzyme complexes tightly regulate gene expression at the chromatin level and have recently been found to colocalize with RNA...

Machine learning models for CT-based classification of ischemic stroke onset time within or beyond 4.5 h: a comparison of approaches.

OBJECTIVES: To compare machine learning models using different combinations of clinical and imaging variables for classifying ischemic stroke patients...

ChatGPT-4o as a diagnostic tool for skin cancer: Diagnostic accuracy in melanoma and non-melanoma detection.

INTRODUCTION: The global incidence of skin cancer is rising, emphasizing the need for early detection tools. Artificial intelligence (AI) models, incl...