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Shattering cancer with quantum machine learning: A preview
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 computa...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8212130/ https://www.ncbi.nlm.nih.gov/pubmed/34179850 http://dx.doi.org/10.1016/j.patter.2021.100281 |
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author | Geraci, Joseph |
author_facet | Geraci, Joseph |
author_sort | Geraci, Joseph |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8212130 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-82121302021-06-25 Shattering cancer with quantum machine learning: A preview Geraci, Joseph Patterns (N Y) Preview 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. Elsevier 2021-06-11 /pmc/articles/PMC8212130/ /pubmed/34179850 http://dx.doi.org/10.1016/j.patter.2021.100281 Text en © 2021 The Author https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Preview Geraci, Joseph Shattering cancer with quantum machine learning: A preview |
title | Shattering cancer with quantum machine learning: A preview |
title_full | Shattering cancer with quantum machine learning: A preview |
title_fullStr | Shattering cancer with quantum machine learning: A preview |
title_full_unstemmed | Shattering cancer with quantum machine learning: A preview |
title_short | Shattering cancer with quantum machine learning: A preview |
title_sort | shattering cancer with quantum machine learning: a preview |
topic | Preview |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8212130/ https://www.ncbi.nlm.nih.gov/pubmed/34179850 http://dx.doi.org/10.1016/j.patter.2021.100281 |
work_keys_str_mv | AT geracijoseph shatteringcancerwithquantummachinelearningapreview |