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When artificial intelligence meets PD-1/PD-L1 inhibitors: Population screening, response prediction and efficacy evaluation.
Jin, Weiqiu; Luo, Qingquan.
Afiliação
  • Jin W; Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China; School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, China.
  • Luo Q; Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China; School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, China. Electronic address: luoqingquan@hotmail.com.
Comput Biol Med ; 145: 105499, 2022 06.
Article em En | MEDLINE | ID: mdl-35439641
ABSTRACT
Programmed cell death protein-1 (PD-1) and its ligand (programmed death ligand 1, PD-L1) inhibitors, as the rising stars of immunotherapy, have been widely used in clinical practice, and the corresponding population screening, response prediction and efficacy evaluation have become increasingly important in clinic. Artificial Intelligence (AI) can help us uncover effective information from clinical data such as medical history, images, laboratory results, sequencing data, etc., which can help us solve above problems and enrich the methodology of clinical research. In this way, AI researches related to PD-1/PD-L1 inhibitors have been emerging. Based on an introduction of AI fundamentals in medicine, this review systematically summarizes the existing AI studies related to PD-1/PD-L1 immunotherapy in three aspects population screening, response prediction and efficacy evaluation, and briefly outlooks the development direction of AI studies related to PD-1/PD-L1 inhibitors.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carcinoma Pulmonar de Células não Pequenas / Neoplasias Pulmonares Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Animals / Humans Idioma: En Revista: Comput Biol Med Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carcinoma Pulmonar de Células não Pequenas / Neoplasias Pulmonares Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Animals / Humans Idioma: En Revista: Comput Biol Med Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China