Dermatology

Feasibility of deep learning-accelerated HASTE-FS for pancreatic cystic lesion surveillance: comparison with conventional HASTE and MRCP.

PURPOSE: Pancreatic cystic lesions (PCL) commonly undergo surveillance using MRI with MR cholangiopancreatography (MRCP). Our objective is to compare the performance of a single-shot fat-saturated T2-weighted technique with deep-learning reconstruction (DL HASTE-FS) to a conventional T2-weighted Half fourier Single-shot Turbo spin-Echo (HASTE) sequence and to MRCP for the purpose of PCL detection,...

ChatGPT-5 vs oral medicine experts for rank-based differential diagnosis of oral lesions: a prospective, biopsy-validated comparison.

Accurate differential diagnosis of oral lesions is challenging. Large language models (LLMs) may support clinicians, but expert-validated evidence on ranked differential lists remains limited. This study aimed to compare ChatGPT-5 with ChatGPT-4o and an oral medicine expert for biopsy-confirmed oral lesions. In this prospective, paired accuracy study, 100 biopsy-confirmed cases with standardized v...

Assessing public interest in artificial intelligence in dermatology: A Google Trends analysis.

Artificial intelligence (AI) is rapidly transforming dermatology, particularly through diagnostic imaging and enhancing patient management. Despite ex...

Artificial intelligence-driven comparative efficacy of topical crisaborole versus halometasone for vitiligo: A randomized and noninferiority study.

A deep learning-based radiomics model for noninvasive diagnosis of melanoma.

To develop a noninvasive diagnostic model integrating deep learning and radiomics for improving the accuracy and clinical utility of early melanoma di...

Transformer-based multi-scale feature fusion for real-time CT bone metastasis detection.

Bone metastasis, a frequent complication of advanced cancers, requires early, precise detection to enable timely interventions and improve patient out...

Machine learning-derived serum protein signatures as biomarkers for checkpoint inhibition in melanoma.

Deep learning for automatic detection of hepatocellular carcinoma in dynamic contrast-enhanced MRI.

OBJECTIVE: Develop a deep learning model for automatic hepatocellular carcinoma (HCC) detection in T1 weighted imaging (WI) Dynamic Contrast-Enhanced ...

Curvature-aware selective feature interaction network for skin lesion segmentation.

With the increasing prevalence of dermatological diseases, skin lesion segmentation has gained significant attention in medical image analysis. Despit...

Machine learning for predicting climate change impacts on Pseudopithomyces chartarum spore counts: a risk indicator of facial eczema.

AIMS: To determine the importance of 11 climate variables on pasture spore count of Pseudopithomyces chartarum, a risk indicator of facial eczema (FE)...

Advancing oral leukoplakia progression recognition: A benchmark with dataset, method, and application.

Oral leukoplakia, a potentially malignant disorder, is a critical precursor to oral squamous cell carcinoma (OSCC), which accounts for 90 % of oral ca...

Artificial Intelligence Use in Acne Diagnosis and Management-A Scoping Review.

Artificial intelligence (AI) techniques can allow for early diagnosis and treatment of acne. Bias in AI model training remains, leading to various cha...

Applications and clinical translation of artificial intelligence in CBCT-based detection of endodontic lesions: a scoping review.

BACKGROUND: Artificial intelligence (AI) especially deep learning (DL) has significantly revolutionized medical image analysis, which include dental d...

Temporal dynamics and predictive modeling of oral epithelial dysplasia features during carcinogenesis.

OBJECTIVE: To investigate the temporal evolution and predictive value of individual histopathological features of oral epithelial dysplasia (OED) duri...

Anatomical, physiological and inflammatory characterization of nonculprit vessels in patients undergoing primary PCI for ST-elevation myocardial infarction in the presence of multivessel disease: Rationale and design of the PICNIC study.

BACKGROUND: Up to 50% of patients presenting with ST-elevation myocardial infarction (STEMI) have multivessel coronary artery disease (CAD). Randomize...

Fully automated multi-sequence detection and alignment of focal liver lesions in dynamic contrast-enhanced MRI.

OBJECTIVES: To validate an artificial intelligence (AI) method for fully automated detection and alignment of focal liver lesions (FLLs) in multi-sequ...

An interactive and explainable AI approach to improve human-machine teaming in cancer subtyping from digital cytopathology.

Algorithmic decision support is rapidly becoming a staple of personalized medicine, particularly for high-stakes recommendations such as cancer subtyp...

Multi-omics technologies: Novel tools and methods for assessing nerve injury and regeneration.

Recently, with the rapid advancement of multi-omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, new tools and app...

AI-Quantified ¹¹C-MET PET/CT bone marrow metabolic activity for prognostic assessment in newly diagnosed multiple myeloma.

PURPOSE: To develop and validate an AI method for automated quantification of whole-skeleton bone marrow (BM) metabolic activity using Carbon 11 (11C)...

Attention-Based Multimodal Deep Learning for Uveal Melanoma Classification Using Ultra-Widefield Fundus Images and Ocular Ultrasound.

PURPOSE: To develop and evaluate a deep learning model that integrates ultra-widefield fundus photography and B-scan ultrasonography for automated cla...