INTRODUCTION: Vitamin D plays a fundamental role in many metabolic pathways, including those involved in cell proliferation and the immune response. Serum levels of this vitamin have been linked to melanoma risk and prognosis. This study aimed to ass...
BACKGROUND: Melanoma is one of the most aggressive types of cancer that has become a world-class problem. According to the World Health Organization estimates, 132,000 cases of the disease and 66,000 deaths from malignant melanoma and other forms of ...
Whole-slide histology images contain information that is valuable for clinical and basic science investigations of cancer but extracting quantitative measurements from these images is challenging for researchers who are not image analysis specialists...
Malignant melanoma (MM) is one of the most dangerous skin cancers. The aim of this study was to present a potential new method for the differential diagnosis of MM from melanocytic naevi (MN). We examined 20 MM and 19 MN with a new ultra-high-frequen...
Histopathological images are widely used to diagnose diseases including skin cancer. As digital histopathological images are typically of very large size, in the order of several billion pixels, automated identification of all abnormal cell nuclei an...
INTRODUCTION: The purpose of this study is to use deep learning and machine learning to learn and classify patients with cutaneous melanoma with different prognoses and to explore the application value of deep learning in the prognosis of cutaneous m...
Computer methods and programs in biomedicine
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BACKGROUND AND OBJECTIVE: In oncology, 18-fluorodeoxyglucose (F-FDG) positron emission tomography (PET) / computed tomography (CT) is widely used to identify and analyse metabolically-active tumours. The combination of the high sensitivity and specif...
OBJECTIVE: The integration of an artificial intelligence tool into pathologists' workflow may lead to a more accurate and timely diagnosis of melanocytic lesions, directly patient care. The objective of this study was to create and evaluate the perfo...
The application of deep learning on whole-slide histological images (WSIs) can reveal insights for clinical and basic tumor science investigations. Finding quantitative imaging biomarkers from WSIs directly for the prediction of disease-free survival...