Skin Cancer

Progressive Transfer Learning and Adversarial Domain Adaptation for Cross-Domain Skin Disease Classification.

Deep learning has been used to analyze and diagnose various skin diseases through medical imaging. H...

Superior skin cancer classification by the combination of human and artificial intelligence.

BACKGROUND: In recent studies, convolutional neural networks (CNNs) outperformed dermatologists in d...

Gabor wavelet-based deep learning for skin lesion classification.

Skin cancer cases are increasing and becoming one of the main problems worldwide. Skin cancer is kno...

Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks.

BACKGROUND: Recently, convolutional neural networks (CNNs) systematically outperformed dermatologist...

Deep neural networks are superior to dermatologists in melanoma image classification.

BACKGROUND: Melanoma is the most dangerous type of skin cancer but is curable if detected early. Rec...

Prediction of melanoma evolution in melanocytic nevi via artificial intelligence: A call for prospective data.

Recent research revealed the superiority of artificial intelligence over dermatologists to diagnose ...

Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images.

BACKGROUND: The diagnosis of most cancers is made by a board-certified pathologist based on a tissue...

Automated identification of malignancy in whole-slide pathological images: identification of eyelid malignant melanoma in gigapixel pathological slides using deep learning.

BACKGROUND/AIMS: To develop a deep learning system (DLS) that can automatically detect malignant mel...

The Application of Deep Learning in the Risk Grading of Skin Tumors for Patients Using Clinical Images.

According to diagnostic criteria, skin tumors can be divided into three categories: benign, low degr...

Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017.

BACKGROUND: Computer vision has promise in image-based cutaneous melanoma diagnosis but clinical uti...

Melanoma Detection by Means of Multiple Instance Learning.

We present an application to melanoma detection of a multiple instance learning (MIL) approach, whos...

Future of Radiotherapy in Nasopharyngeal Carcinoma.

Nasopharyngeal carcinoma (NPC) is a malignancy with unique clinical biological profiles such as asso...

ASO Author Reflections: Robotic Pelvic Lymph Node Dissection for Metastatic Melanoma-A Minimally Invasive Approach to a Difficult Problem.

Detection of Skin Cancer Using SVM, Random Forest and kNN Classifiers.

Most common and deadly type of cancer is Skin cancer. The destructive kind of cancers in skin is Mel...

Assessing the effectiveness of artificial intelligence methods for melanoma: A retrospective review.

BACKGROUND: Artificial intelligence methods for the classification of melanoma have been studied ext...

Enhanced classifier training to improve precision of a convolutional neural network to identify images of skin lesions.

BACKGROUND: In recent months, multiple publications have demonstrated the use of convolutional neura...

IAPSO-AIRS: A novel improved machine learning-based system for wart disease treatment.

Wart disease (WD) is a skin illness on the human body which is caused by the human papillomavirus (H...

Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer.

Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptio...

Capturing the differences between humoral immunity in the normal and tumor environments from repertoire-seq of B-cell receptors using supervised machine learning.

BACKGROUND: The recent success of immunotherapy in treating tumors has attracted increasing interest...

MHCSeqNet: a deep neural network model for universal MHC binding prediction.

BACKGROUND: Immunotherapy is an emerging approach in cancer treatment that activates the host immune...

Pathologist-level classification of histopathological melanoma images with deep neural networks.

BACKGROUND: The diagnosis of most cancers is made by a board-certified pathologist based on a tissue...