Journal of the American Academy of Dermatology
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J. Am. Acad. Dermatol. · Jun 2020
Comparative StudyWhere you live matters: Regional differences in health care resource use for psoriasis in the United States.
It is unknown which U.S. Census region offers the best access to health care resources. ⋯ Southern U.S. states have the greatest access to biologic medications and incurred fewer ambulatory and ED visits. The Midwest had the lowest access to biologic medications and ambulatory and ED care. The West incurred the lowest total health care costs, while the Northeast incurred the highest total health care costs.
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J. Am. Acad. Dermatol. · May 2020
ReviewDeep learning for dermatologists: Part I. Fundamental concepts.
Artificial intelligence is generating substantial interest in the field of medicine. One form of artificial intelligence, deep learning, has led to rapid advances in automated image analysis. In 2017, an algorithm demonstrated the ability to diagnose certain skin cancers from clinical photographs with the accuracy of an expert dermatologist. ⋯ Although experts will never be replaced by artificial intelligence, it will certainly affect the specialty of dermatology. In this first article of a 2-part series, the basic concepts of deep learning will be reviewed with the goal of laying the groundwork for effective communication between clinicians and technical colleagues. In part 2 of the series, the clinical applications of deep learning in dermatology will be reviewed and limitations and opportunities will be considered.
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J. Am. Acad. Dermatol. · May 2020
ReviewDeep learning for dermatologists: Part II. Current applications.
Because of a convergence of the availability of large data sets, graphics-specific computer hardware, and important theoretical advancements, artificial intelligence has recently contributed to dramatic progress in medicine. One type of artificial intelligence known as deep learning has been particularly impactful for medical image analysis. ⋯ In this second article of a 2-part series, we review the existing and emerging clinical applications of deep learning in dermatology and discuss future opportunities and limitations. Part 1 of this series offered an introduction to the basic concepts of deep learning to facilitate effective communication between clinicians and technical experts.