Dermatology

Multi-site validation of an AI-based biomarker test for determining ER, PR, and HER2 status from H&E-stained breast cancer slides.

BACKGROUND: The assessment of estrogen/progesterone receptors (ER/PR) and human epidermal growth factor receptor 2 (HER2) is essential for managing breast cancer (BC) patients, as these biomarkers guide targeted therapies. Traditional methods such as immunohistochemistry (IHC) and in situ hybridisation (ISH) are widely used, but they are resource-intensive and time-consuming. To address these chal...

Sharing a whole-/total-body [18F]FDG-PET/CT dataset with CT-derived segmentations: an ENHANCE.PET initiative.

We present a large whole-body and total-body curated dataset of dual-modality 2-deoxy-2-[18F]fluoro-D-glucose (FDG)-Positron Emission Tomography/Computed Tomography (PET/CT) studies, consisting of 1,683 PET/CT images and the corresponding CT-derived segmentations of 130 target regions. This multi-center dataset includes images from individuals without overt disease and patients with a range of mal...

Synergistic Multi-Magnification Fusion Network for Tongue Image-Based Oral Cancer Diagnosis.

Oral cancer represents a critical global public health concern, where accurate and timely early detection is paramount. While deep learning on non-inv...

Actinic keratosis staging in multimodal image data.

BACKGROUND AND OBJECTIVE: Actinic Keratosis (AK) is a common skin condition, usually appearing on sun-exposed areas, whose progression is associated w...

High-throughput strategy for targeting MDM2 in uveal melanoma to reverse radiation therapy resistance.

Uveal melanoma (UM) presents a formidable clinical challenge due to its marked resistance to radiotherapy. In this study, an integrative strategy comb...

Genomic Determinants of Response to Alpelisib Plus Fulvestrant in the SOLAR-1 Trial.

BACKGROUND: Approximately 40% of patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-), advanced br...

Post-translational modification signature shapes the tumor immune microenvironment and predicts clinical outcomes in melanoma.

Lesion Learning Network with Relation Aware Transformer for Diabetic Retinopathy Grading.

Diabetic Retinopathy (DR) is a leading cause of permanent blindness due to the difficulty of early screening. In this context, deep-learning-based aut...

Comprehensive Assessment of Artificial Intelligence as a Stand-alone tool for Cervical Cancer Screening Using a 50% Negative Cutoff Value.

PURPOSE: An emerging application of artificial intelligence (AI) in cervical cytology is its use as an independent screener for triaging cases that do...

Next-generation epidermal patches: Bridging 3D and multidimensional printing for biomedical and personal care innovations.

Advances in additive manufacturing, particularly 3D and multidimensional printing, have enabled unprecedented control over the architecture, compositi...

Integration of advanced ultrasound techniques, radiomics, and artificial intelligence for improved diagnosis of cystic breast lesions.

Cystic breast lesions are commonly encountered on breast ultrasound, encompassing a spectrum from simple benign cysts to complex mixed solid and cysti...

Predicting Melanoma Impact on the Swedish Healthcare System from the Adult Population Using Machine Learning on Registry Data.

Melanoma incidence has increased in Western countries over the past 50 years, leading to significant healthcare costs. In Sweden, comprehensive health...

Unsupervised clustering of clinical and laboratory features of systemic lupus erythematosus: insights from a multicentre cohort.

OBJECTIVE: This study explored the relationship between clinical phenotypes and immuno-molecular features of systemic lupus erythematosus (SLE) using ...

MSF-VMDNet for multi class segmentation of skin cancer whole slide images using a multi frequency dual encoder network.

Skin cancer has become a global public health issue. Dermoscopy is a routine diagnostic method; however, to improve accuracy, it is often combined wit...

EnamelNet-TRiX: A Lesion-Aware Dual-Transformer With Cross-Attention for Early and Advanced Enamel Caries Diagnosis.

PURPOSE: Dental caries is one of the most prevalent oral diseases worldwide, and predicting Early Enamel Caries (EEC) and Advanced Enamel Caries (AEC)...

irAE-GPT: leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasets.

BACKGROUND: Large language models (LLMs) have emerged as transformative technologies, revolutionising natural language understanding and generation ac...

Artificial Intelligence in Skin Inflammation and Oncology: Diagnostic Innovations in Dermatology.

Skin cancer is a prevalent public health problem worldwide, caused by multiple factors like ultraviolet (UV) radiation, environmental toxins, and life...

A Review of Automatic Hair Removal in Dermoscopy Images: From Image Processing to Deep Learning.

Early melanoma detection is made possible by dermoscopy, but automated analysis and clinical evaluation are often hampered by hair artifacts in images...

Text guided cross attentive multimodal learning with visual feature modulation for automated skin lesion detection.

Automated skin lesion detection is essential for early dermatological diagnosis. Most deep learning algorithms employ dermoscopic images and ignore th...

Smart medical system integrating clinical workflows for robust skin cancer detection across heterogeneous pathologies.

Skin cancer is among the most prevalent and life-threatening dermatological diseases worldwide, with melanoma responsible for a substantial proportion...