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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-9405970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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