Radiogenomics for Precision Medicine With a Big Data Analytics Perspective.


Journal

IEEE journal of biomedical and health informatics
ISSN: 2168-2208
Titre abrégé: IEEE J Biomed Health Inform
Pays: United States
ID NLM: 101604520

Informations de publication

Date de publication:
09 2019
Historique:
pubmed: 1 1 2019
medline: 18 1 2020
entrez: 1 1 2019
Statut: ppublish

Résumé

Precision medicine promises better healthcare delivery by improving clinical practice. Using evidence-based substratification of patients, the objective is to achieve better prognosis, diagnosis, and treatment that will transform existing clinical pathways toward optimizing care for the specific needs of each patient. The wealth of today's healthcare data, often characterized as big data, provides invaluable resources toward new knowledge discovery that has the potential to advance precision medicine. The latter requires interdisciplinary efforts that will capitalize the information, know-how, and medical data of newly formed groups fusing different backgrounds and expertise. The objective of this paper is to provide insights with respect to the state-of-the-art research in precision medicine. More specifically, our goal is to highlight the fundamental challenges in emerging fields of radiomics and radiogenomics by reviewing the case studies of Cancer and Alzheimer's disease, describe the computational challenges from a big data analytics perspective, and discuss standardization and open data initiatives that will facilitate the adoption of precision medicine methods and practices.

Identifiants

pubmed: 30596591
doi: 10.1109/JBHI.2018.2879381
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2063-2079

Auteurs

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Classifications MeSH