Dermatology

Image Quality Assessment of Abdominal CT by Use of New Deep Learning Image Reconstruction: Initial Experience.

The purpose of this study was to perform quantitative and qualitative evaluation of a deep learning...

New Auxiliary Function with Properties in Nonsmooth Global Optimization for Melanoma Skin Cancer Segmentation.

In this paper, an algorithm is introduced to solve the global optimization problem for melanoma skin...

A machine learning algorithm for simulating immunohistochemistry: development of SOX10 virtual IHC and evaluation on primarily melanocytic neoplasms.

Immunohistochemistry (IHC) is a diagnostic technique used throughout pathology. A machine learning a...

Addressing class imbalance in deep learning for small lesion detection on medical images.

Deep learning methods utilizing Convolutional Neural Networks (CNNs) have led to dramatic advances i...

Augmented Intelligence Dermatology: Deep Neural Networks Empower Medical Professionals in Diagnosing Skin Cancer and Predicting Treatment Options for 134 Skin Disorders.

Although deep learning algorithms have demonstrated expert-level performance, previous efforts were ...

[The future of AI in dermatology and of dermatology with AI].

What is AI? Applications of artificial intelligence to dermatology.

In the past, the skills required to make an accurate dermatological diagnosis have required exposure...

Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.

OBJECTIVES: We develop and validate a radiomics model based on multiparametric magnetic resonance im...

CPFNet: Context Pyramid Fusion Network for Medical Image Segmentation.

Accurate and automatic segmentation of medical images is a crucial step for clinical diagnosis and a...

Artificial Intelligence in Dermatology: A Primer.

Artificial intelligence is becoming increasingly important in dermatology, with studies reporting ac...

Deep Learning-Based Methods for Automatic Diagnosis of Skin Lesions.

The main purpose of the study was to develop a high accuracy system able to diagnose skin lesions us...

Triple-Negative Breast Cancer: A Review of Conventional and Advanced Therapeutic Strategies.

Triple-negative breast cancer (TNBC) cells are deficient in estrogen, progesterone and ERBB2 recepto...

Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data.

BACKGROUND: The ability to confidently predict health outcomes from gene expression would catalyze a...

Sulodexide modulates the dialysate effect on the peritoneal mesothelium.

Peritoneal membrane damage during chronic peritoneal dialysis is the main cause of that treatment fa...

Skin Lesion Segmentation from Dermoscopic Images Using Convolutional Neural Network.

Clinical treatment of skin lesion is primarily dependent on timely detection and delimitation of les...

Artificial intelligence in dermatology: the 'unsupervised' learning.

Semi-Supervised Nests of Melanocytes Segmentation Method Using Convolutional Autoencoders.

In this research, we present a semi-supervised segmentation solution using convolutional autoencoder...

DePicT Melanoma Deep-CLASS: a deep convolutional neural networks approach to classify skin lesion images.

BACKGROUND: Melanoma results in the vast majority of skin cancer deaths during the last decades, eve...

The impact of iterative reconstruction algorithms on machine learning-based coronary CT angiography-derived fractional flow reserve (CT-FFR) values.

To evaluate the impact of an iterative reconstruction (IR) algorithm (advanced modeled iterative rec...

Artificial neural networks allow response prediction in squamous cell carcinoma of the scalp treated with radiotherapy.

BACKGROUND: Epithelial neoplasms of the scalp account for approximately 2% of all skin cancers and f...

Towards Interpretable Skin Lesion Classification with Deep Learning Models.

Skin disease is a prevalent condition all over the world. Computer vision-based technology for autom...