Katherine M. Stiff, Matthew J. Franklin, Yufei Zhou, Anant Madabhushi, Thomas J. Knackstedt
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Artificial intelligence and melanoma: A comprehensive review of clinical, dermoscopic, and histologic applications
Melanoma detection, prognosis, and treatment represent challenging and complex areas of cutaneous oncology with considerable impact on patient outcomes and healthcare economics. Artificial intelligence (AI) applications in these tasks are rapidly developing. Neural networks with increasing levels of sophistication are being implemented in clinical image, dermoscopic image, and histopathologic specimen classification of pigmented lesions. These efforts hold promise of earlier and highly accurate melanoma detection, as well as reliable prognostication and prediction of therapeutic response. Herein, we provide a brief introduction to AI, discuss contemporary investigational applications of AI in melanoma, and summarize challenges encountered with AI.
期刊介绍：
Pigment Cell & Melanoma Researchpublishes manuscripts on all aspects of pigment cells including development, cell and molecular biology, genetics, diseases of pigment cells including melanoma. Papers that provide insights into the causes and progression of melanoma including the process of metastasis and invasion, proliferation, senescence, apoptosis or gene regulation are especially welcome, as are papers that use the melanocyte system to answer questions of general biological relevance. Papers that are purely descriptive or make only minor advances to our knowledge of pigment cells or melanoma in particular are not suitable for this journal. Keywords
Pigment Cell & Melanoma Research, cell biology, melatonin, biochemistry, chemistry, comparative biology, dermatology, developmental biology, genetics, hormones, intracellular signalling, melanoma, molecular biology, ocular and extracutaneous melanin, pharmacology, photobiology, physics, pigmentary disorders
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