Publicly available skin image datasets are increasingly used to develop machine learning
algorithms for skin cancer diagnosis. However, the total number of datasets and their …

Skin cancer is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …

How does the accuracy of deep neural network models trained to classify clinical images of
skin conditions vary across skin color? While recent studies demonstrate computer vision …

Despite significant progress in the past few years, machine learning systems are still often
viewed as" black boxes", which lack the ability to explain their output decisions. In high …

There is limited access to effective cervical cancer screening programs in many resource‐
limited settings, resulting in continued high cervical cancer burden. Human papillomavirus …

Congenital heart disease (CHD) is the most common type of birth defect. Without timely
detection and treatment, approximately one-third of children with CHD would die in the infant …

Melanoma detection, prognosis, and treatment represent challenging and complex areas of
cutaneous oncology with considerable impact on patient outcomes and healthcare …

The incidence of melanoma is increasing rapidly. This cancer has a good prognosis if
detected early. For this reason, various systems of skin lesion image analysis, which support …

Utilization of digital technologies for cataract screening in primary care is a potential solution
for addressing the dilemma between the growing aging population and unequally …

Dermatological classification algorithms developed without sufficiently diverse training data
may generalize poorly across populations. While intentional data collection and annotation …