Dermatology

Plasma Exosome Analysis for Protein Mutation Identification Using a Combination of Raman Spectroscopy and Deep Learning.

Protein mutation detection using liquid biopsy can be simply performed periodically, making it easy ...

A deep learning framework for quantitative analysis of actin microridges.

Microridges are evolutionarily conserved actin-rich protrusions present on the apical surface of squ...

Dermatology in the wake of an AI revolution: Who gets a say?

MM-GLCM-CNN: A multi-scale and multi-level based GLCM-CNN for polyp classification.

Distinguishing malignant from benign lesions has significant clinical impacts on both early detectio...

Exploring Dual-Energy CT Spectral Information for Machine Learning-Driven Lesion Diagnosis in Pre-Log Domain.

In this study, we proposed a computer-aided diagnosis (CADx) framework under dual-energy spectral CT...

The complex ethics of applying ChatGPT and language model artificial intelligence in dermatology.

Deep learning in computational dermatopathology of melanoma: A technical systematic literature review.

Deep learning (DL) has become one of the major approaches in computational dermatopathology, evidenc...

Image quality and lesion detectability of deep learning-accelerated T2-weighted Dixon imaging of the cervical spine.

OBJECTIVES: To validate the subjective image quality and lesion detectability of deep learning-accel...

Biologically Interpretable Deep Learning To Predict Response to Immunotherapy In Advanced Melanoma Using Mutations and Copy Number Variations.

Only 30-40% of advanced melanoma patients respond effectively to immunotherapy in clinical practice,...

Deep Learning-Based Computer-Aided Diagnosis for Breast Lesion Classification on Ultrasound: A Prospective Multicenter Study of Radiologists Without Breast Ultrasound Expertise.

Computer-aided diagnosis (CAD) systems for breast ultrasound interpretation have been primarily eva...

Automated 3-dimensional MRI segmentation for the posterosuperior rotator cuff tear lesion using deep learning algorithm.

INTRODUCTION: Rotator cuff tear (RCT) is a challenging and common musculoskeletal disease. Magnetic ...

Boosting multiple sclerosis lesion segmentation through attention mechanism.

Magnetic resonance imaging is a fundamental tool to reach a diagnosis of multiple sclerosis and moni...

Deep learning-based PET/MR radiomics for the classification of annualized relapse rate in multiple sclerosis.

Background Annualized Relapse Rate (ARR) is one of the most important indicators of disease progress...

Semi-Supervised CT Lesion Segmentation Using Uncertainty-Based Data Pairing and SwapMix.

Semi-supervised learning (SSL) methods show their powerful performance to deal with the issue of dat...

HER2-low breast cancer: insights on pathological testing.

Human epidermal growth factor receptor 2 (HER2) is an important biomarker for predicting prognosis a...

Deep learning detection of melanoma metastases in lymph nodes.

BACKGROUND: In melanoma patients, surgical excision of the first draining lymph node, the sentinel l...

Progressive growing of Generative Adversarial Networks for improving data augmentation and skin cancer diagnosis.

Early melanoma diagnosis is the most important factor in the treatment of skin cancer and can effect...

Adrenal lesion classification with abdomen caps and the effect of ROI size.

Accurate classification of adrenal lesions on magnetic resonance (MR) images are very important for ...

Dynamic hierarchical multi-scale fusion network with axial MLP for medical image segmentation.

Medical image segmentation provides various effective methods for accuracy and robustness of organ s...

Deep learning radiomics model based on breast ultrasound video to predict HER2 expression status.

PURPOSE: The detection of human epidermal growth factor receptor 2 (HER2) expression status is essen...

Rema-Net: An efficient multi-attention convolutional neural network for rapid skin lesion segmentation.

For clinical treatment, the accurate segmentation of lesions from dermoscopic images is extremely va...