Dermatology

Application of Deep Learning on the Prognosis of Cutaneous Melanoma Based on Full Scan Pathology Images.

INTRODUCTION: The purpose of this study is to use deep learning and machine learning to learn and cl...

Artificial intelligence in the detection of skin cancer.

Recent advances in artificial intelligence (AI) in dermatology have demonstrated the potential to im...

Background selection schema on deep learning-based classification of dermatological disease.

Skin diseases are one of the most common ailments affecting humans. Artificial intelligence based on...

Deep Convolutional Generative Adversarial Networks to Enhance Artificial Intelligence in Healthcare: A Skin Cancer Application.

In recent years, researchers designed several artificial intelligence solutions for healthcare appli...

Deep learning-based classification of dermatological lesions given a limited amount of labelled data.

BACKGROUND: Artificial intelligence (AI) techniques are promising in early diagnosis of skin disease...

Noncirrhotic Portal Hypertension after Trastuzumab Emtansine in HER2-positive Breast Cancer as Determined by Deep Learning-measured Spleen Volume at CT.

Background Trastuzumab emtansine (T-DM1) is an antibody-drug conjugate approved for use in human epi...

Double-Balanced Loss for Imbalanced Colorectal Lesion Classification.

Colorectal cancer has a high incidence rate in all countries around the world, and the survival rate...

A shallow deep learning approach to classify skin cancer using down-scaling method to minimize time and space complexity.

The complex feature characteristics and low contrast of cancer lesions, a high degree of inter-class...

A New Approach to Quantify and Grade Radiation Dermatitis Using Deep-Learning Segmentation in Skin Photographs.

AIMS: Objective evaluation of radiation dermatitis is important for analysing the correlation betwee...

Design of predictive model to optimize the solubility of Oxaprozin as nonsteroidal anti-inflammatory drug.

These days, many efforts have been made to increase and develop the solubility and bioavailability o...

A Novel Deep Learning Model to Distinguish Malignant Versus Benign Solid Lung Nodules.

BACKGROUND In this study we aimed to establish a new transfer learning model based on noncontrast an...

Validation of a Denoising Method Using Deep Learning-Based Reconstruction to Quantify Multiple Sclerosis Lesion Load on Fast FLAIR Imaging.

BACKGROUND AND PURPOSE: Accurate quantification of WM lesion load is essential for the care of patie...

Unsupervised Deep Learning for Stroke Lesion Segmentation on Follow-up CT Based on Generative Adversarial Networks.

BACKGROUND AND PURPOSE: Supervised deep learning is the state-of-the-art method for stroke lesion se...

SCDNet: A Deep Learning-Based Framework for the Multiclassification of Skin Cancer Using Dermoscopy Images.

Skin cancer is a deadly disease, and its early diagnosis enhances the chances of survival. Deep lear...

Commentary: Using the ROSA Robot for Lesion Resection: A Novel Adapter With Added Applications.

Novel aspects of Raman spectroscopy in skin research.

The analytical technology of Raman spectroscopy has an almost 100-year history. During this period, ...

Gene Identification and Potential Drug Therapy for Drug-Resistant Melanoma with Bioinformatics and Deep Learning Technology.

BACKGROUND: Melanomas are skin malignant tumors that arise from melanocytes which are primarily trea...

Machine learning for multi-parametric breast MRI: radiomics-based approaches for lesion classification.

In the artificial intelligence era, machine learning (ML) techniques have gained more and more impor...

An automatic method to quantify trichomes in Arabidopsis thaliana.

Trichomes are unicellular or multicellular hair-like appendages developed on the aerial plant epider...

Histologic Screening of Malignant Melanoma, Spitz, Dermal and Junctional Melanocytic Nevi Using a Deep Learning Model.

OBJECTIVE: The integration of an artificial intelligence tool into pathologists' workflow may lead t...

Validating Automatic Concept-Based Explanations for AI-Based Digital Histopathology.

Digital histopathology poses several challenges such as label noise, class imbalance, limited availa...