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Artificial Intelligence Approach in Melanoma

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Melanoma

Abstract

Since its inception in the mid-twentieth century, the field of artificial intelligence (AI) has undergone numerous transformations and retreats. Using large datasets, powerful computers, and modern computational methods, the subset of AI known as machine learning can identify complex patterns in real-world data, yielding observations, associations, and predictions that can match or exceed human capabilities. After decades of promise, the field stands poised to influence a broad range of human endeavors, from the most complex strategic games to autonomous vehicle navigation, financial engineering, and health care. Therefore, the purpose of this chapter is to provide an introduction to AI approaches and medical applications while elaborating on the role of AI in malignant melanoma detection and diagnosis from a healthcare provider and consumer perspective. It is critical that we continue to balance the opportunity and threat of AI in malignant melanoma, as this technology becomes more robust to maximize an effective implementation.

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Acknowledgments

We thank Delaney Stratton, RN for her valuable editorial and artistic support.

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Correspondence to Clara Curiel-Lewandrowski .

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© 2019 Springer Science+Business Media, LLC, part of Springer Nature

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Curiel-Lewandrowski, C. et al. (2019). Artificial Intelligence Approach in Melanoma. In: Fisher, D., Bastian, B. (eds) Melanoma. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7147-9_43

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  • DOI: https://doi.org/10.1007/978-1-4614-7147-9_43

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-7148-6

  • Online ISBN: 978-1-4614-7147-9

  • eBook Packages: MedicineReference Module Medicine

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