Dermatology

Prognostic value of a combined model integrating clinical and PET radiomics parameters in metastatic melanoma: A dual-center retrospective study.

OBJECTIVES: To develop and evaluate the predictive efficacy of a combined model incorporating clinic...

Low-count whole-body PET denoising with deep learning in a multicenter, multi-tracer and externally validated study.

BACKGROUND: Positron Emission Tomography (PET) is a powerful diagnostic tool, but its availability, ...

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

Artificial intelligence (AI) is rapidly transforming dermatology, particularly through diagnostic im...

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 ...

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 T...

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

With the increasing prevalence of dermatological diseases, skin lesion segmentation has gained signi...

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...

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 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...

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

OBJECTIVE: To investigate the temporal evolution and predictive value of individual histopathologica...

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 ali...

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...

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 ma...

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 photog...

coPERCIST: AI-assisted PET-CT response assessment.

PURPOSE: The PET Response Criteria in Solid Tumours (PERCIST) 1.0 provides a standardized framework ...

AI-assisted basal cell carcinoma diagnosis with LC-OCT: A multicentric retrospective study.

BACKGROUND: Basal cell carcinoma (BCC) is the most common skin cancer, requiring an early diagnosis ...

High-Risk Carotid Lesion Segmentation: Advancing Stroke Risk Detection With Deep Learning.

INTRODUCTION: While the benefits of carotid surgery for symptomatic carotid artery disease are well-...

Deep learning enhanced label-free cervical screening via stimulated Raman cytology.

Cervical cancer screening remains pivotal for early detection and effective disease management, yet ...

Predicting sentinel lymph node metastasis in melanoma patients: A machine learning-based predictive model.

BACKGROUND: Risk factors for sentinel lymph node (SLN) metastasis in melanoma have been studied. How...

Artificial intelligence predicts c-KIT exon 11 genotype by phenotype in canine cutaneous mast cell tumors: Can human observers learn it?

Canine cutaneous mast cell tumors (ccMCTs) are frequent neoplasms with variable biological behaviors...