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Cutting-Edge AI Technologies Meet Precision Medicine to Improve Cancer Care

To provide precision medicine for better cancer care, researchers must work on clinical patient data, such as electronic medical records, physiological measurements, biochemistry, computerized tomography scans, digital pathology, and the genetic landscape of cancer tissue. To interpret big biodata i...

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Detalles Bibliográficos
Autores principales: Lin, Peng-Chan, Tsai, Yi-Shan, Yeh, Yu-Min, Shen, Meng-Ru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9405970/
https://www.ncbi.nlm.nih.gov/pubmed/36009026
http://dx.doi.org/10.3390/biom12081133
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author Lin, Peng-Chan
Tsai, Yi-Shan
Yeh, Yu-Min
Shen, Meng-Ru
author_facet Lin, Peng-Chan
Tsai, Yi-Shan
Yeh, Yu-Min
Shen, Meng-Ru
author_sort Lin, Peng-Chan
collection PubMed
description To provide precision medicine for better cancer care, researchers must work on clinical patient data, such as electronic medical records, physiological measurements, biochemistry, computerized tomography scans, digital pathology, and the genetic landscape of cancer tissue. To interpret big biodata in cancer genomics, an operational flow based on artificial intelligence (AI) models and medical management platforms with high-performance computing must be set up for precision cancer genomics in clinical practice. To work in the fast-evolving fields of patient care, clinical diagnostics, and therapeutic services, clinicians must understand the fundamentals of the AI tool approach. Therefore, the present article covers the following four themes: (i) computational prediction of pathogenic variants of cancer susceptibility genes; (ii) AI model for mutational analysis; (iii) single-cell genomics and computational biology; (iv) text mining for identifying gene targets in cancer; and (v) the NVIDIA graphics processing units, DRAGEN field programmable gate arrays systems and AI medical cloud platforms in clinical next-generation sequencing laboratories. Based on AI medical platforms and visualization, large amounts of clinical biodata can be rapidly copied and understood using an AI pipeline. The use of innovative AI technologies can deliver more accurate and rapid cancer therapy targets.
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spelling pubmed-94059702022-08-26 Cutting-Edge AI Technologies Meet Precision Medicine to Improve Cancer Care Lin, Peng-Chan Tsai, Yi-Shan Yeh, Yu-Min Shen, Meng-Ru Biomolecules Review To provide precision medicine for better cancer care, researchers must work on clinical patient data, such as electronic medical records, physiological measurements, biochemistry, computerized tomography scans, digital pathology, and the genetic landscape of cancer tissue. To interpret big biodata in cancer genomics, an operational flow based on artificial intelligence (AI) models and medical management platforms with high-performance computing must be set up for precision cancer genomics in clinical practice. To work in the fast-evolving fields of patient care, clinical diagnostics, and therapeutic services, clinicians must understand the fundamentals of the AI tool approach. Therefore, the present article covers the following four themes: (i) computational prediction of pathogenic variants of cancer susceptibility genes; (ii) AI model for mutational analysis; (iii) single-cell genomics and computational biology; (iv) text mining for identifying gene targets in cancer; and (v) the NVIDIA graphics processing units, DRAGEN field programmable gate arrays systems and AI medical cloud platforms in clinical next-generation sequencing laboratories. Based on AI medical platforms and visualization, large amounts of clinical biodata can be rapidly copied and understood using an AI pipeline. The use of innovative AI technologies can deliver more accurate and rapid cancer therapy targets. MDPI 2022-08-17 /pmc/articles/PMC9405970/ /pubmed/36009026 http://dx.doi.org/10.3390/biom12081133 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Lin, Peng-Chan
Tsai, Yi-Shan
Yeh, Yu-Min
Shen, Meng-Ru
Cutting-Edge AI Technologies Meet Precision Medicine to Improve Cancer Care
title Cutting-Edge AI Technologies Meet Precision Medicine to Improve Cancer Care
title_full Cutting-Edge AI Technologies Meet Precision Medicine to Improve Cancer Care
title_fullStr Cutting-Edge AI Technologies Meet Precision Medicine to Improve Cancer Care
title_full_unstemmed Cutting-Edge AI Technologies Meet Precision Medicine to Improve Cancer Care
title_short Cutting-Edge AI Technologies Meet Precision Medicine to Improve Cancer Care
title_sort cutting-edge ai technologies meet precision medicine to improve cancer care
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9405970/
https://www.ncbi.nlm.nih.gov/pubmed/36009026
http://dx.doi.org/10.3390/biom12081133
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