Literature DB >> 33160512

Precision medicine and artificial intelligence: overview and relevance to reproductive medicine.

Iman Hajirasouliha1, Olivier Elemento2.   

Abstract

Traditionally, new treatments have been developed for the population at large. Recently, large-scale genomic sequencing analyses have revealed tremendous genetic diversity between individuals. In diseases driven by genetic events such as cancer, genomic sequencing can unravel all the mutations that drive individual tumors. The ability to capture the genetic makeup of individual patients has led to the concept of precision medicine, a modern, technology-driven form of personalized medicine. Precision medicine matches each individual to the best treatment in a way that is tailored to his or her genetic uniqueness. To further personalize medicine, precision medicine increasingly incorporates and integrates data beyond genomics, such as epigenomics and metabolomics, as well as imaging. Increasingly, the robust use and integration of these modalities in precision medicine require the use of artificial intelligence and machine learning. This modern view of precision medicine, adopted early in certain areas of medicine such as cancer, has started to impact the field of reproductive medicine. Here we review the concepts and history of precision medicine and artificial intelligence, highlight their growing impact on reproductive medicine, and outline some of the challenges and limitations that these new fields have encountered in medicine.
Copyright © 2020. Published by Elsevier Inc.

Entities:  

Keywords:  Precision medicine; artificial intelligence; reproductive medicine

Mesh:

Year:  2020        PMID: 33160512     DOI: 10.1016/j.fertnstert.2020.09.156

Source DB:  PubMed          Journal:  Fertil Steril        ISSN: 0015-0282            Impact factor:   7.329


  2 in total

1.  Three ways of knowing: the integration of clinical expertise, evidence-based medicine, and artificial intelligence in assisted reproductive technologies.

Authors:  Gerard Letterie
Journal:  J Assist Reprod Genet       Date:  2021-04-19       Impact factor: 3.357

2.  Artificial intelligence-the future is now.

Authors:  Mark P Trolice; Carol Curchoe; Alexander M Quaas
Journal:  J Assist Reprod Genet       Date:  2021-07-07       Impact factor: 3.412

  2 in total

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