Dermatology

Application of Semi-supervised Fuzzy Clustering Based on Knowledge Weighting and Cluster Center Learning to Mammary Molybdenum Target Image Segmentation.

Breast cancer is commonly diagnosed with mammography. Using image segmentation algorithms to separat...

Image Quality and Lesion Detectability of Pancreatic Phase Thin-Slice Computed Tomography Images With a Deep Learning-Based Reconstruction Algorithm.

OBJECTIVE: To evaluate the image quality and lesion detectability of pancreatic phase thin-slice com...

Combining hyperspectral imaging techniques with deep learning to aid in early pathological diagnosis of melanoma.

BACKGROUND: Cutaneous melanoma, an exceedingly aggressive form of skin cancer, holds the top rank in...

A CT-based Deep Learning Radiomics Nomogram for the Prediction of EGFR Mutation Status in Head and Neck Squamous Cell Carcinoma.

RATIONALE AND OBJECTIVES: Accurately assessing epidermal growth factor receptor (EGFR) mutation stat...

The role of artificial intelligence language models in dermatology: Opportunities, limitations and ethical considerations.

Prediction of lymphoma response to CAR T cells by deep learning-based image analysis.

Clinical prognostic scoring systems have limited utility for predicting treatment outcomes in lympho...

Deep-learning visualization enhancement method for optical coherence tomography angiography in dermatology.

Optical coherence tomography angiography (OCTA) in dermatology usually suffers from low image qualit...

ChatGPT-4: dermatology aid in the emergency room.

Deep Learning-Based Skin Lesion Multi-class Classification with Global Average Pooling Improvement.

Cancerous skin lesions are one of the deadliest diseases that have the ability in spreading across o...

High accuracy epidermal growth factor receptor mutation prediction via histopathological deep learning.

BACKGROUND: The detection of epidermal growth factor receptor (EGFR) mutations in patients with non-...

Automated dermatoscopic pattern discovery by clustering neural network output for human-computer interaction.

A deep attention LSTM embedded aggregation network for multiple histopathological images.

Recent advancements in computer vision and neural networks have facilitated the medical imaging surv...

Artificial Intelligence Applied to a First Screening of Naevoid Melanoma: A New Use of Fast Random Forest Algorithm in Dermatopathology.

Malignant melanoma (MM) is the "great mime" of dermatopathology, and it can present such rare varian...

Deep learning to automatically evaluate HER2 gene amplification status from fluorescence in situ hybridization images.

Human epidermal growth factor receptor 2 (HER2) gene amplification helps identify breast cancer pati...

The chatbots are coming: Risks and benefits of consumer-facing artificial intelligence in clinical dermatology.

Interpretable HER2 scoring by evaluating clinical guidelines through a weakly supervised, constrained deep learning approach.

The evaluation of the Human Epidermal growth factor Receptor-2 (HER2) expression is an important pro...

The role of artificial intelligence in dermatology: the promising but limited accuracy of ChatGPT in diagnosing clinical scenarios.

A survey on deep learning for skin lesion segmentation.

Skin cancer is a major public health problem that could benefit from computer-aided diagnosis to red...

Joint liver and hepatic lesion segmentation in MRI using a hybrid CNN with transformer layers.

UNLABELLED: Backgound and Objective: Deep learning-based segmentation of the liver and hepatic lesio...

Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases.

BACKGROUND: Recent advances in digital pathology have enabled accurate and standardised enumeration ...

Deep learning for predicting future lesion emergence in high-risk breast MRI screening: a feasibility study.

BACKGROUND: International societies have issued guidelines for high-risk breast cancer (BC) screenin...