Dermatology

Editorial: New Target for Skin Cancer.

Skin cancer encompasses a diverse spectrum of malignancies with increasing global incidence and persistent clinical challenges. Despite advances in therapies such as immune checkpoint inhibitors and targeted agents, many patients-especially those with rare subtypes or immunologically 'cold' tumours-face limited options and poor outcomes. This special issue of Experimental Dermatology, titled 'New ...

Deep learning for liver lesion segmentation and classification on staging CT scans of colorectal cancer patients: a multi-site technical validation study.

AIM: To validate a liver lesion detection and classification model using staging computed tomography (CT) scans of colorectal cancer (CRC) patients.

GAN Inversion for Data Augmentation to Improve Colonoscopy Lesion Classification.

A major challenge in applying deep learning to medical imaging is the paucity of annotated data. This study explores the use of synthetic images for d...

Scale-Aware Super-Resolution Network With Dual Affinity Learning for Lesion Segmentation From Medical Images.

Convolutional neural networks (CNNs) have shown remarkable progress in medical image segmentation. However, the lesion segmentation remains a challeng...

Skin Cancer Detection Using Deep Learning Approaches.

This review examined multiple deep learning (DL) methods, including artificial neural networks (ANNs), convolutional neural networks (CNNs), k-neares...

Self-HER2Net: A generative self-supervised framework for HER2 classification in IHC histopathology of breast cancer.

Breast cancer is a significant global health concern, where precise identification of proteins like Human Epidermal Growth Factor Receptor 2 (HER2) in...

Impact of artificial intelligence assisted lesion detection on radiologists' interpretation at multiparametric prostate MRI.

PURPOSE: To compare prostate cancer lesion detection using conventional and artificial intelligence (AI)-assisted image interpretation at multiparamet...

Deep learning for multiple sclerosis lesion classification and stratification using MRI.

BACKGROUND AND OBJECTIVE: Multiple sclerosis (MS) is a chronic neurological disease characterized by inflammation, demyelination, and neurodegeneratio...

A new diagnostic method and tool for cutaneous leishmaniasis based on artificial intelligence techniques.

BACKGROUND: Cutaneous leishmaniasis (CL) is a parasitic disease caused by protozoan parasites of the genus Leishmania, leading to significant morbidit...

Improving skin lesion classification through saliency-guided loss functions.

Deep learning has significantly advanced computer-aided diagnosis, particularly in skin lesion classification. However, achieving high classification ...

Self-supervised multi-modality learning for multi-label skin lesion classification.

BACKGROUND: The clinical diagnosis of skin lesions involves the analysis of dermoscopic and clinical modalities. Dermoscopic images provide detailed v...

Exploring the toxicological impact of bisphenol a exposure on psoriasis through network toxicology, machine learning, and multi-dimensional bioinformatics analysis.

Psoriasis is a common immune - mediated skin disease, the pathogenesis of which is not completely elucidated. Environmental factors are key to its ons...

Artificial intelligence in predicting EGFR mutations from whole slide images in lung Cancer: A systematic review and Meta-Analysis.

BACKGROUND: Epidermal growth factor receptor (EGFR) mutations play a pivotal role in guiding targeted therapy for lung cancer, making their accurate d...

Comprehensive biobanking strategy with clinical impact at the European Cancer Moonshot Lund Center.

This white paper presents a comprehensive biobanking framework developed at the European Cancer Moonshot Lund Center that merges rigorous sample handl...

Deep Learning-Based Breast Cancer Detection in Mammography: A Multi-Center Validation Study in Thai Population

This study presents a deep learning system for breast cancer detection in mammography, developed using a modified EfficientNetV2 architecture with e...

Skin Lesion Phenotyping via Nested Multi-modal Contrastive Learning

We introduce SLIMP (Skin Lesion Image-Metadata Pre-training) for learning rich representations of skin lesions through a novel nested contrastive le...

Synthetic Generation and Latent Projection Denoising of Rim Lesions in Multiple Sclerosis

Quantitative susceptibility maps from magnetic resonance images can provide both prognostic and diagnostic information in multiple sclerosis, a neur...

Machine learning based differential diagnosis of SAPHO syndrome and secondary bone tumors using whole body bone scintigraphy.

SAPHO syndrome is an inflammatory disorder with bone and cutaneous manifestations, for which whole-body bone scintigraphy (WBBS) is frequently used in...

Integrating SEResNet101 and SE-VGG19 for advanced cervical lesion detection: a step forward in precision oncology.

BACKGROUND: Cervical cancer remains a significant global health issue, with accurate differentiation between low-grade (LSIL) and high-grade squamous ...

Differentiation of canine and feline neoplasms using multi-modal imaging and machine learning.

Canine/feline (sub-)cutaneous tumors, which include lipomas, mastocytomas and soft tissue sarcomas, introduce diagnostic challenges due to inherent ti...