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Open Access 24-05-2023 | Artificial Intelligence | Review

The artificial intelligence and machine learning in lung cancer immunotherapy

Authors: Qing Gao, Luyu Yang, Mingjun Lu, Renjing Jin, Huan Ye, Teng Ma

Published in: Journal of Hematology & Oncology | Issue 1/2023

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Abstract

Since the past decades, more lung cancer patients have been experiencing lasting benefits from immunotherapy. It is imperative to accurately and intelligently select appropriate patients for immunotherapy or predict the immunotherapy efficacy. In recent years, machine learning (ML)-based artificial intelligence (AI) was developed in the area of medical-industrial convergence. AI can help model and predict medical information. A growing number of studies have combined radiology, pathology, genomics, proteomics data in order to predict the expression levels of programmed death-ligand 1 (PD-L1), tumor mutation burden (TMB) and tumor microenvironment (TME) in cancer patients or predict the likelihood of immunotherapy benefits and side effects. Finally, with the advancement of AI and ML, it is believed that "digital biopsy" can replace the traditional single assessment method to benefit more cancer patients and help clinical decision-making in the future. In this review, the applications of AI in PD-L1/TMB prediction, TME prediction and lung cancer immunotherapy are discussed.
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Metadata
Title
The artificial intelligence and machine learning in lung cancer immunotherapy
Authors
Qing Gao
Luyu Yang
Mingjun Lu
Renjing Jin
Huan Ye
Teng Ma
Publication date
24-05-2023
Publisher
BioMed Central
Published in
Journal of Hematology & Oncology / Issue 1/2023
Electronic ISSN: 1756-8722
DOI
https://doi.org/10.1186/s13045-023-01456-y

ASH 2024 Annual Meeting Coverage

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In this webinar, Professor Martin Dreyling and an esteemed international panel of CAR T-cell therapy experts discuss the latest data on the safety, efficacy, and clinical impact of CAR T-cell therapies in the treatment of r/r DLBCL and r/r FL.

Please note, this webinar is not intended for healthcare professionals based in the US and UK.

Sponsored by:
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Chaired by: Prof. Martin Dreyling
Developed by: Springer Healthcare
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