Dermatology

Deep learning approaches for bone and bone lesion segmentation on 18FDG PET/CT imaging in the context of metastatic breast cancer.

FDG PET/CT imaging is commonly used in diagnosis and follow-up of metastatic breast cancer, but its quantitative analysis is complicated by the number and location heterogeneity of metastatic lesions. Considering that bones are the most common location among metastatic sites, this work aims to compare different approaches to segment the bones and bone metastatic lesions in breast cancer.Two deep l...

The value of convolutional neural networks in the diagnosis of melanoma simulators.

Patient Perspectives on the Use of Artificial Intelligence for Skin Cancer Screening: A Qualitative Study.

IMPORTANCE: The use of artificial intelligence (AI) is expanding throughout the field of medicine. In dermatology, researchers are evaluating the pote...

Can artificial intelligence replace manual search for systematic literature? Review on cutaneous manifestations in primary Sjögren's syndrome.

OBJECTIVES: Manual systematic literature reviews are becoming increasingly challenging due to the sharp rise in publications. The primary objective of...

Research Techniques Made Simple: Deep Learning for the Classification of Dermatological Images.

Deep learning is a branch of artificial intelligence that uses computational networks inspired by the human brain to extract patterns from raw data. D...

[Prediction of gene mutation in lung cancer based on deep learning and histomorphology analysis].

Lung cancer is a most common malignant tumor of the lung and is the cancer with the highest morbidity and mortality worldwide. For patients with advan...

Artificial Intelligence in Dermatology-Where We Are and the Way to the Future: A Review.

Although artificial intelligence has been available for some time, it has garnered significant interest recently and has been popularized by major com...

Determination of Electrocution Using Fourier Transform Infrared Microspectroscopy and Machine Learning Algorithm.

Objective To analyze the differences among electrical damage, burns and abrasions in pig skin using Fourier transform infrared microspectroscopy （FTIR...

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 challenging because various anatomic structures create c...

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

BACKGROUND: Staphylococcus aureus is a gram-positive spherical bacterium commonly present in nasal fossae and in the skin of healthy people; however, ...

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

For computer-aided diagnosis (CAD), detection, segmentation, and classification from medical imagery are three key components to efficiently assist ph...

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 convolutional neural network (CNN). The proposed method ...

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 instability and accumulation of multiple molecular alternat...

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 pigment lesion analysis. It has gained the attention ...

Comparative Study in Efficacy and Safety of Intralesional Injections of Vitamin D3, Measles Rubella (MR) Vaccine, and Purified Protein Derivative (PPD) in the Management of Cutaneous Warts.

INTRODUCTION: Cutaneous warts caused by human papillomavirus are the most common dermatological diseases being contagious, recurrent, and recalcitrant...

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 results in classifying Multiple Sclerosis (MS) patient...

[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 carcinoma (BCC) and pigmented nevi in Chinese by usin...

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 subtypes of renal cell carcinoma (clear cell, papillary...

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 measures for treatment planning such as lesion summ...