Computer methods and programs in biomedicine
33862570
BACKGROUND AND OBJECTIVE: The purpose of the present study was to investigate low-shot deep learning models applied to conjunctival melanoma detection using a small dataset with ocular surface images.
Computational and mathematical methods in medicine
35669372
The objective of this study was to explore the image classification and case characteristics of pigmented nevus (PN) diagnosed by dermoscopy under deep learning. 268 patients were included as the research objects and they were randomly divided into o...
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...
BACKGROUND: Cutaneous melanoma, an exceedingly aggressive form of skin cancer, holds the top rank in both malignancy and mortality among skin cancers. In early stages, distinguishing malignant melanomas from benign pigmented nevi pathologically becom...
INTRODUCTION: Melanocytic nevi present microscopic patterns, which differ in their associated melanoma risk, and can be non-invasively recognized under Reflectance Confocal Microscopy (RCM).
Melanoma is still a major health problem worldwide. Early diagnosis is the first step toward reducing its mortality, but it remains a challenge even for experienced dermatologists. Although computer-aided systems have been developed to help diagnosis...
INTRODUCTION: Melanocytic nevi (MN), warts, seborrheic keratoses (SK), and psoriasis are four common types of skin surface lesions that typically require dermatoscopic examination for definitive diagnosis in clinical dermatology settings. This proces...