PersPective | FOCUS https://doi.org/10.1038/s41591-018-0316-z 1Stanford University, Stanford, CA, USA. 2Google Research, San Jose, CA, USA. 3These authors contributed equally: Andre Esteva, Alexandre Robicquet. *e-mail: andre.esteva@gmail.com Deep learning1, a subfield of machine learning (ML), has seen a dramatic resurgence in the past 6 years, largely driven by increases in computational power and the availability of mas- sive new datasets. The field has witnessed striking advances in the ability of machines to understand and manipulate data, including images2, language3, and speech4. Healthcare and medicine stand to benefit immensely from deep learning because of the sheer volume of data being generated (150 exabytes or 1018 bytes in United States alone, growing 48% annually5) as well as the increasing proliferation of medical devices and digital record systems. ML is distinct from other types of computer programming in that it transforms the inputs of an algori
