RESUMO
We developed a digital tool for home-based monitoring of skin disease, our digital tool. In the current observational pilot study, we found that DORA is feasible to use in practice, as it has a high patient compliance, retention and satisfaction. Clinicans rated the photos generally good quality or perfect quality. These results show that the digital health tool DORA can easily be used by patients to send photos to their dermatologist, which could reduce unnecessary clinical visits. It may also be used in other settings where digital literacy barriers and unequal access to dermatologists contribute to healthcare disparities.
RESUMO
Recent advances in artificial intelligence research have led to an increase in the development of algorithms for detecting malignancies from clinical and dermoscopic images of skin diseases. These methods are dependent on the collection of training and testing data. There are important considerations when acquiring skin images and data for translational artificial intelligence research. In this paper, we discuss the best practices and challenges for light photography image data collection, covering ethics, image acquisition, labeling, curation, and storage. The purpose of this work is to improve artificial intelligence for malignancy detection by supporting intentional data collection and collaboration between subject matter experts, such as dermatologists and data scientists.