Dermatology

A deep learning approach to direct immunofluorescence pattern recognition in autoimmune bullous diseases.

BACKGROUND: Artificial intelligence (AI) is reshaping healthcare, using machine and deep learning (D...

Potential of Multimodal Large Language Models for Data Mining of Medical Images and Free-text Reports

Medical images and radiology reports are crucial for diagnosing medical conditions, highlighting t...

TransCell: In Silico Characterization of Genomic Landscape and Cellular Responses by Deep Transfer Learning.

Gene expression profiling of new or modified cell lines becomes routine today; however, obtaining co...

Unravelling tumour cell diversity and prognostic signatures in cutaneous melanoma through machine learning analysis.

Melanoma, a highly malignant tumour, presents significant challenges due to its cellular heterogenei...

Lesion Segmentation in Skin Cancer Images using Fusion Model via Deep Learning Networks.

Skin cancer, one of the most prevalent and life-threatening cancers globally, has become a focus of ...

Enhancing Choroidal Nevus Position Identification through CNN-Based Segmentation of Eye Fundus Images.

Diagnosing choroidal nevus in color fundus images is challenging for clinicians not regularly practi...

Channel Fitting Network for Retinal Lesion Segmentation from OCT Images.

Retinal lesion is a cause of age-related macular degeneration that poses a big threat to elderly pop...

Visual In-Context Learning for Few-Shot Eczema Segmentation.

Automated diagnosis of eczema from digital camera images is crucial for applications that allow pati...

Beyond Dysplasia: Uncovering Structure in Oral Potentially Malignant Diseases with Unsupervised Contrastive Learning.

Automated cancer diagnosis research often focuses on a binary task - recognize dysplasia and cancer ...

Derm-T2IM: Harnessing Synthetic Skin Lesion Data via Stable Diffusion Models for Enhanced Skin Disease Classification using ViT and CNN.

This study explores the utilization of Dermatoscopic synthetic data generated through stable diffusi...

Concordance in basal cell carcinoma diagnosis. Building a proper ground truth to train Artificial Intelligence tools

Background: The existence of different basal cell carcinoma (BCC) clinical criteria cannot be obje...

Artificial intelligence for automatic detection of basal cell carcinoma from frozen tissue tangential biopsies.

Evaluation of basal cell carcinoma (BCC) involves tangential biopsies of a suspicious lesion that is...

Artificial intelligence-empowered cellular morphometric risk score improves prognostic stratification of cutaneous squamous cell carcinoma.

BACKGROUND: Risk stratification of cutaneous squamous cell carcinoma (cSCC) is essential for managin...

Advancing dermatology: embracing the power of artificial intelligence. Comment on 'Artificial intelligence-assisted publishing in five prominent dermatology journals: a quantitative study of recent publications'.

Classifying real-world macroscopic images in the primary-secondary care interface using transfer learning: implications for development of artificial intelligence solutions using nondermoscopic images.

BACKGROUND: The application of deep learning (DL) to diagnostic dermatology has been the subject of ...

Artificial intelligence-generated patient information leaflets: a comparison of contents according to British Association of Dermatologists standards.

BACKGROUND: Patient information leaflets (PILs) can supplement a clinical consultation and provide a...

Evaluation of an artificial intelligence-based decision support for the detection of cutaneous melanoma in primary care: a prospective real-life clinical trial.

BACKGROUND: Use of artificial intelligence (AI), or machine learning, to assess dermoscopic images o...

Location-based Radiology Report-Guided Semi-supervised Learning for Prostate Cancer Detection

Prostate cancer is one of the most prevalent malignancies in the world. While deep learning has po...

Development and Validation of Fully Automatic Deep Learning-Based Algorithms for Immunohistochemistry Reporting of Invasive Breast Ductal Carcinoma

Immunohistochemistry (IHC) analysis is a well-accepted and widely used method for molecular subtyp...

Performance evaluation of ML models for preoperative prediction of HER2-low BC based on CE-CBBCT radiomic features: A prospective study.

To explore the value of machine learning (ML) models based on contrast-enhanced cone-beam breast com...

[Artificial intelligence research advances in discrimination and diagnosis of pulmonary ground-glass nodules].

Lung cancer, which accounts for about 18% of all cancer-related deaths worldwide, has a dismal 5-yea...