Dermatology, Data and Informatics AND High-Risk Skin Cancer
DERMATOLOGY, DATA AND INFORMATICS (Roberto Novoa, MD)
The ability to capture, store, and analyze vast amounts of data has revolutionized human endeavors, and medicine is no exception. Information technology has touched every aspect of medicine, and this influence will only grow over time. However, a clinical dermatologist in practice today only sees the surface of this influence, through interactions with electronic medical records or through patients bringing the results of Internet searches to their visits. He or she will often miss the vast underlying structures that gird our system, that spur its advances, and that will continue to change the way we care for our patients. In this issue, we hope to shed light on these underlying methods, detailing the various roles of information technology in dermatology and what may lie ahead.
HIGH-RISK SKIN CANCER (Siegrid Yu, MD)
The majority of nonmelanoma skin cancers have excellent prognosis and are effectively treated with local, minimally invasive surgical or destructive techniques. However, the rising incidence of skin cancer combined with lengthened survival of the elderly, immunosuppressed, and at-risk populations has resulted in an increasing number of locally advanced, regional, and distantly metastatic disease. This subset of high-risk cases results in significant morbidity and mortality. As experts in skin cancers, dermatologists are at the forefront of the diagnosis, management, and investigation of novel therapies. Accurate diagnosis, risk stratification, staging, and a multidisciplinary approach are critical for optimizing patient outcome. Thank you to our colleagues in medical, surgical, and radiation oncology for the collaborative care of our most challenging patients.
In recent years, the development of targeted molecular therapy and immunotherapy has revolutionized the treatment of locally advanced and metastatic disease. I would like to thank the contributing authors for summarizing the advances in the field and providing us with knowledge regarding the management of high-risk skin cancer patients.
The application of artificial intelligence (AI) to medicine has considerable potential within dermatology, where the majority of diagnoses are based on visual pattern recognition.
The role of public challenges and data sets towards algorithm development, trust, and use in clinical practice
In the past decade, machine learning and artificial intelligence have made significant advancements in pattern analysis, including speech and natural language processing, image recognition, object detection, facial recognition, and action categorization.
In this chapter, we present the use of whole slide imaging (WSI) and dermoscopy in the field of dermatology. Image digitization has allowed for increasing computer-assisted clinical decision-making.
MoleMapper: an application for crowdsourcing mole images to advance melanoma early-detection research
Advancements in smartphone technologies and the use of specialized health care applications offer an exciting new era to promote melanoma awareness to the public and improve education and prevention strategies.
Emerging technologies for health information in dermatology: opportunities and drawbacks of web-based searches, social media, mobile applications, and direct-to-consumer genetic testing in patient care
Emerging technology is fundamentally changing how individuals interact with the health care system.