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Artificial intelligence in cancer immunotherapy: Applications in neoantigen recognition, antibody design and immunotherapy response prediction.
Li, Tong; Li, Yupeng; Zhu, Xiaoyi; He, Yao; Wu, Yanling; Ying, Tianlei; Xie, Zhi.
Afiliación
  • Li T; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.
  • Li Y; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.
  • Zhu X; MOE/NHC Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infectious Disease and Biosecurity, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, China; Shanghai Engineering Research Center for Synthetic Immunology, Shanghai, China.
  • He Y; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.
  • Wu Y; MOE/NHC Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infectious Disease and Biosecurity, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, China; Shanghai Engineering Research Center for Synthetic Immunology, Shanghai, China.
  • Ying T; MOE/NHC Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infectious Disease and Biosecurity, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, China; Shanghai Engineering Research Center for Synthetic Immunology, Shanghai, China. Electronic ad
  • Xie Z; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China; Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China. Electronic address: xiezhi@gmail.com.
Semin Cancer Biol ; 91: 50-69, 2023 06.
Article en En | MEDLINE | ID: mdl-36870459
ABSTRACT
Cancer immunotherapy is a method of controlling and eliminating tumors by reactivating the body's cancer-immunity cycle and restoring its antitumor immune response. The increased availability of data, combined with advancements in high-performance computing and innovative artificial intelligence (AI) technology, has resulted in a rise in the use of AI in oncology research. State-of-the-art AI models for functional classification and prediction in immunotherapy research are increasingly used to support laboratory-based experiments. This review offers a glimpse of the current AI applications in immunotherapy, including neoantigen recognition, antibody design, and prediction of immunotherapy response. Advancing in this direction will result in more robust predictive models for developing better targets, drugs, and treatments, and these advancements will eventually make their way into the clinical setting, pushing AI forward in the field of precision oncology.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Neoplasias Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Semin Cancer Biol Asunto de la revista: NEOPLASIAS Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Neoplasias Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Semin Cancer Biol Asunto de la revista: NEOPLASIAS Año: 2023 Tipo del documento: Article País de afiliación: China