Dermatology

Deep Learning Approaches Towards Skin Lesion Segmentation and Classification from Dermoscopic Images - A Review.

BACKGROUND: Automated intelligent systems for unbiased diagnosis are primary requirement for the pig...

Detecting anomalous growth of skin lesion using threshold-based segmentation algorithm and Fuzzy K-Nearest Neighbor classifier.

CONTEXT: Skin cancer is a complex and life-threatening disease caused primarily by genetic instabili...

Is artificial intelligence going to replace dermatologists?

The use of computers or machines in medicine dates back to the 1960s. Deep learning software program...

Lesion Image Synthesis Using DCGANs for Metastatic Liver Cancer Detection.

This chapter proposes a method to detect metastatic liver cancer from X-ray CT images using a convol...

Deep Learning Computer-Aided Diagnosis for Breast Lesion in Digital Mammogram.

For computer-aided diagnosis (CAD), detection, segmentation, and classification from medical imagery...

Studies for Bacterystic Evaluation against of 2-Naphthoic Acid Analogues.

BACKGROUND: Staphylococcus aureus is a gram-positive spherical bacterium commonly present in nasal f...

Keratinocytic Skin Cancer Detection on the Face Using Region-Based Convolutional Neural Network.

IMPORTANCE: Detection of cutaneous cancer on the face using deep-learning algorithms has been challe...

Artificial intelligence for melanoma diagnosis: how can we deliver on the promise?

MRI-based prediction of conversion from clinically isolated syndrome to clinically definite multiple sclerosis using SVM and lesion geometry.

Neuroanatomical pattern classification using support vector machines (SVMs) has shown promising resu...

[Clinical image identification of basal cell carcinoma and pigmented nevi based on convolutional neural network].

To construct an intelligent assistant diagnosis model based on the clinical images of basal cell car...

Artificial intelligence in dermatology: past, present, and future.

Skin Lesion Detection with Support Vector Machines on iOS Devices.

Automated wound detection has become a common issue in health care. A broad variety of image process...

Enhancing Case Capture, Quality, and Completeness of Primary Melanoma Pathology Records via Natural Language Processing.

PURPOSE: Medical records contain a wealth of useful, informative data points valuable for clinical r...

Artificial Intelligence Estimates the Importance of Baseline Factors in Predicting Response to Anti-PD1 in Metastatic Melanoma.

OBJECTIVE: Prognosis of patients with metastatic melanoma has dramatically improved over recent year...

Automated Detection of Measurements and Their Descriptors in Radiology Reports Using a Hybrid Natural Language Processing Algorithm.

Radiological measurements are reported in free text reports, and it is challenging to extract such m...

The Classification of Renal Cancer in 3-Phase CT Images Using a Deep Learning Method.

In this research, we exploit an image-based deep learning framework to distinguish three major subty...

Convolutional Neural Network Approach to Classify Skin Lesions Using Reflectance Confocal Microscopy.

We propose an approach based on a convolutional neural network to classify skin lesions using the re...

Deep Learning for Automating the Organization of Institutional Dermatology Image Stores.

A common challenge faced by researchers associated with healthcare institutions is that data of inte...

Light Field Image Dataset of Skin Lesions.

Light field imaging technology has been attracting increasing interest because it enables capturing ...

Boundary-aware Semi-supervised Deep Learning for Breast Ultrasound Computer-Aided Diagnosis.

Breast ultrasound (US) is an effective imaging modality for breast cancer diagnosis. US computer-aid...

Selection of Radiomics Features based on their Reproducibility.

Dimensionality reduction is key to alleviate machine learning artifacts in clinical applications wit...