Preparing next-generation scientists for biomedical big data

Artificial intelligence approaches

Jason H. Moore, Mary Regina Boland, Pablo G. Camara, Hannah Chervitz, Graciela Gonzalez, Blanca E. Himes, Dokyoon Kim, Danielle L. Mowery, Marylyn D. Ritchie, Li Shen, Ryan J. Urbanowicz, John H. Holmes

Research output: Contribution to journalReview article

Abstract

Personalized medicine is being realized by our ability to measure biological and environmental information about patients. Much of these data are being stored in electronic health records yielding big data that presents challenges for its management and analysis. Here, we review several areas of knowledge that are necessary for next-generation scientists to fully realize the potential of biomedical big data. We begin with an overview of big data and its storage and management. We then review statistics and data science as foundational topics followed by a core curriculum of artificial intelligence, machine learning and natural language processing that are needed to develop predictive models for clinical decision making. We end with some specific training recommendations for preparing next-generation scientists for biomedical big data.

Original languageEnglish (US)
Pages (from-to)247-257
Number of pages11
JournalPersonalized Medicine
Volume16
Issue number3
DOIs
StatePublished - Jan 1 2019
Externally publishedYes

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Natural Language Processing
Precision Medicine
Electronic Health Records
Information Storage and Retrieval
Artificial Intelligence
Curriculum
Clinical Decision-Making
Machine Learning

ASJC Scopus subject areas

  • Molecular Medicine
  • Pharmacology

Cite this

Moore, J. H., Boland, M. R., Camara, P. G., Chervitz, H., Gonzalez, G., Himes, B. E., ... Holmes, J. H. (2019). Preparing next-generation scientists for biomedical big data: Artificial intelligence approaches. Personalized Medicine, 16(3), 247-257. https://doi.org/10.2217/pme-2018-0145

Preparing next-generation scientists for biomedical big data : Artificial intelligence approaches. / Moore, Jason H.; Boland, Mary Regina; Camara, Pablo G.; Chervitz, Hannah; Gonzalez, Graciela; Himes, Blanca E.; Kim, Dokyoon; Mowery, Danielle L.; Ritchie, Marylyn D.; Shen, Li; Urbanowicz, Ryan J.; Holmes, John H.

In: Personalized Medicine, Vol. 16, No. 3, 01.01.2019, p. 247-257.

Research output: Contribution to journalReview article

Moore, JH, Boland, MR, Camara, PG, Chervitz, H, Gonzalez, G, Himes, BE, Kim, D, Mowery, DL, Ritchie, MD, Shen, L, Urbanowicz, RJ & Holmes, JH 2019, 'Preparing next-generation scientists for biomedical big data: Artificial intelligence approaches', Personalized Medicine, vol. 16, no. 3, pp. 247-257. https://doi.org/10.2217/pme-2018-0145
Moore, Jason H. ; Boland, Mary Regina ; Camara, Pablo G. ; Chervitz, Hannah ; Gonzalez, Graciela ; Himes, Blanca E. ; Kim, Dokyoon ; Mowery, Danielle L. ; Ritchie, Marylyn D. ; Shen, Li ; Urbanowicz, Ryan J. ; Holmes, John H. / Preparing next-generation scientists for biomedical big data : Artificial intelligence approaches. In: Personalized Medicine. 2019 ; Vol. 16, No. 3. pp. 247-257.
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