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Research and application of omics and artificial intelligence in cancer.
Zhang, Ye; Ma, Wenwen; Huang, Zhiqiang; Liu, Kun; Feng, Zhaoyi; Zhang, Lei; Li, Dezhi; Mo, Tianlu; Liu, Qing.
Afiliación
  • Zhang Y; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China.
  • Ma W; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China.
  • Huang Z; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China.
  • Liu K; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China.
  • Feng Z; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China.
  • Zhang L; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China.
  • Li D; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China.
  • Mo T; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China.
  • Liu Q; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China.
Phys Med Biol ; 69(21)2024 Oct 18.
Article en En | MEDLINE | ID: mdl-39079556
ABSTRACT
Cancer has a high incidence and lethality rate, which is a significant threat to human health. With the development of high-throughput technologies, different types of cancer genomics data have been accumulated, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics. A comprehensive analysis of various omics data is needed to understand the underlying mechanisms of tumor development. However, integrating such a massive amount of data is one of the main challenges today. Artificial intelligence (AI) techniques such as machine learning are now becoming practical tools for analyzing and understanding multi-omics data on diseases. Enabling great optimization of existing research paradigms for cancer screening, diagnosis, and treatment. In addition, intelligent healthcare has received widespread attention with the development of healthcare informatization. As an essential part of innovative healthcare, practical, intelligent prognosis analysis and personalized treatment for cancer patients are also necessary. This paper introduces the advanced multi-omics data analysis technology in recent years, presents the cases and advantages of the combination of both omics data and AI applied to cancer diseases, and finally briefly describes the challenges faced by multi-omics analysis and AI at the current stage, aiming to provide new perspectives for oncology research and the possibility of personalized cancer treatment.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Genómica / Neoplasias Límite: Humans Idioma: En Revista: Phys Med Biol Año: 2024 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Genómica / Neoplasias Límite: Humans Idioma: En Revista: Phys Med Biol Año: 2024 Tipo del documento: Article Pais de publicación: Reino Unido