Dermatology

Automated diagnosis of keratitis from low-quality slit-lamp images using an improved generative adversarial network.

Keratitis is a major cause of visual impairment worldwide, with timely and accurate diagnosis being critical to preventing irreversible vision loss. Existing deep learning (DL) models rely heavily on high-quality slit-lamp (HQS) images, limiting their applicability in real-world clinical scenarios where low-quality slit-lamp (LQS) images are frequently encountered due to acquisition-related artifa...

A machine-learning-derived multi-cell death mode signature predicts melanoma prognosis and reveals an immune-cold tumor microenvironment.

BACKGROUND: Regulated cell death programs influence melanoma progression and antitumor immunity, yet a robust prognostic model integrating multiple cell-death modalities remains limited. METHODS: Transcriptomic and clinical data from TCGA and independent GEO cohorts (GSE19234, GSE22153, and GSE65904) were analyzed. Activity of diverse cell-death programs was quantified using ssGSEA/GSVA. Prognosti...

Refined AI-ASPECTS with modified atlas and lesion-load thresholds: advancing acute ischemic stroke imaging and prognostic prediction.

BACKGROUND: The artificial intelligence-assisted ASPECTS (AI-ASPECTS) system has become an increasingly common tool in clinical practice for assessing...

Deep learning versus general dentists: a clinical evaluation of caries diagnostic accuracy on bitewing radiographs.

BACKGROUND: The diagnostic accuracy of caries detection on bitewing radiographs varies among dentists and is strongly influenced by lesion severity. I...

ADC Target Profiling in NSCLC: Generalizable AI Separates TROP-2 and cMET Phenotypes.

PURPOSE: Antibody-drug conjugates (ADC) targeting trophoblast cell surface antigen 2 (TROP-2) and cMET are entering clinical trials in non-small cell ...

Optimization of hypovascular liver lesion detectability in dual-energy CT using deep learning image reconstruction: a phantom study for potential iodine dose reduction.

OBJECTIVE: To determine the optimal low-keV level using deep learning image reconstruction (DLIR) that maximizes lesion detectability, and to assess t...

An Ultra-Lightweight Cross-scale Attention Mamba Network for Accurate Skin Lesion Segmentation.

Accurate skin lesion segmentation is essential for the early detection and effective management of skin cancer. Existing deep learning architectures a...

AI in clinical diagnostics in dermatology: applications, validation, and real-world use cases.

Artificial intelligence (AI) has moved from proof-of-concept studies in dermatology to selective, real-world clinical use, particularly in image-based...

Artificial Intelligence in skin disease therapeutics: from drug discovery to personalized treatment pathways.

Artificial intelligence (AI) comprises computational methods capable of tasks associated with human cognition, and includes specialized subfields such...

Psoriatic Disease Across Dimensions: Global Epidemiology, Comorbidity, and Artificial Intelligence in Treatment Prediction.

The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2025 annual meeting featured a new "Soapbox: Rapid fire presentati...

A Systematic Evaluation of Image Preprocessing in Deep Learning Detection and Segmentation of Intracranial Metastatic Disease.

BACKGROUND AND PURPOSE: Image preprocessing is an essential, though often overlooked, part of machine learning, and it is unclear how preprocessing te...

A framework based on hybrid Suzuki-Abe and convex Hull approach for improved classification of skin lesions.

Skin cancer is among the most common and dangerous forms of cancer worldwide. The earlier stage lesions, if not diagnosed on time, transform into canc...

Reducing skin tone bias in dermatology AI via sketch-guided multimodal fusion.

AI-driven skin lesion diagnosis systems are revolutionizing dermatology practice but perform worse on darker skin populations, which threatens diagnos...

Application of a deep learning method based on CBCT panoramic reconstruction images for differentiating operationally defined cystic and neoplastic jaw lesions from osteomyelitis: a single-center retrospective study.

This single-center retrospective study developed and internally validated a two-dimensional deep learning model based on cone-beam computed tomography...

Attention augmented feature fusion in a hybrid CNN-transformer for fine-grained diabetic retinopathy severity grading.

Despite the advent of automated diabetic retinopathy (DR) severity grading from retinal fundus images, it remains challenging because of class imbalan...

Automatic lesion segmentation in ⁶⁸Ga-PSMA PET/CT and ¹⁷⁷Lu-PSMA SPECT/CT: added value of PET-guided SPECT in a bicentric study.

BACKGROUND: Manual segmentation of prostate cancer metastases on PSMA PET/CT and SPECT/CT is time-consuming and poorly scalable, particularly in highl...

Preclinical and Virtual Models of Mucosal Melanoma: Bridging Translational Gaps in a Rare and Lethal Cancer.

Mucosal melanoma (MM) is a rare and lethal subtype of melanoma, disproportionately affecting Asian populations and exhibiting distinct clinicopatholog...

Blinded, bias-controlled multi-rater evaluation of human-versus-AI brain metastasis segmentation using a hybrid foundation-model framework.

BACKGROUND: Accurate segmentation of brain metastases (BM) is essential for diagnosis, stereotactic radiosurgery planning, and longitudinal assessment...

ChatGPT-Generated Advice on Sun Protection and Skin Cancer Prevention Compared to American Academy of Dermatology Guidelines: Cross-Sectional Content Analysis.

BACKGROUND: Artificial intelligence tools such as ChatGPT are increasingly used by the public to seek health-related information. However, the accurac...

Artificial intelligence (AI)-assisted diagnosis of skin diseases: From image classification to dermatology-specific multimodal clinical reasoning.

Artificial intelligence (AI) in dermatology has moved beyond the early paradigm of single-image classification. Dermatological diagnosis is achieved b...