Shattering cancer with quantum machine learning: A preview.


Journal

Patterns (New York, N.Y.)
ISSN: 2666-3899
Titre abrégé: Patterns (N Y)
Pays: United States
ID NLM: 101767765

Informations de publication

Date de publication:
11 Jun 2021
Historique:
entrez: 28 6 2021
pubmed: 29 6 2021
medline: 29 6 2021
Statut: epublish

Résumé

Machine learning has become a standard tool for medical researchers attempting to model disease in various ways, including building models to predict response to medications, classifying disease subtypes, and discovering new therapies. In this preview, we review a paper that utilizes quantum computation in order to tackle a critical issue that exists with medical datasets: they are small, in that they contain few samples. The authors' work demonstrates the possibility that these quantum-based methods may provide an advantage for small datasets and thus have a real impact for medical researchers in the future.

Identifiants

pubmed: 34179850
doi: 10.1016/j.patter.2021.100281
pii: S2666-3899(21)00114-8
pmc: PMC8212130
doi:

Types de publication

News

Langues

eng

Pagination

100281

Informations de copyright

© 2021 The Author.

Déclaration de conflit d'intérêts

J.G. is a founder and major shareholder of NetraMark Corp, a company working with medical data for the purpose of optimizing drug discovery and development.

Auteurs

Joseph Geraci (J)

Department of Molecular Medicine, Queen's University, Kingston, ON, Canada.
Centre for Biotechnology and Genomics Medicine, Medical College of Georgia, Augusta, GA, USA.
NetraMark Corp, Toronto, ON, Canada.

Classifications MeSH