“Properly leveraged AI-based techniques could herald a new era of precision medicine guided by non-invasive, imaging-based disease evaluation.”
Credit: McGale et al.
“Properly leveraged AI-based techniques could herald a new era of precision medicine guided by non-invasive, imaging-based disease evaluation.”
BUFFALO, NY- August 27, 2024 – A new editorial was published in Oncotarget’s Volume 15 on August 26, 2024, entitled, “Artificial intelligence: A transformative tool in precision oncology.”
Artificial intelligence (AI) is revolutionizing society and healthcare, opening new possibilities for precision medicine. In oncology, immunotherapy (IO) has similarly transformed cancer treatment with novel therapeutic mechanisms, but it has also introduced atypical response patterns that challenge traditional evaluation methods.
In this editorial, researchers Jeremy McGale, Matthew J. Liao, Egesta Lopci, Aurélien Marabelle, and Laurent Dercle from the Department of Radiology at Columbia University in New York, explore AI’s role in addressing these challenges. They focus on the development of new biomarkers for precise disease characterization, particularly those using imaging for the early response assessment of cancer patients treated with IO.
Additionally, the researchers highlight a comprehensive review that applied AI/radiomics to cross-sectional imaging (PET, CT, MRI) showcasing the current landscape in IO treatment. They also determined that of 87 relevant studies, most utilized algorithms to predict treatment response or prognosticate survival at predetermined time points.
“In conclusion, although AI/Radiomics in IO is a rapidly advancing field, there remains significant room for improvement.”
Correspondence to: Jeremy McGale – jm4782@cumc.columbia.edu, and Laurent Dercle – ld2752@cumc.columbia.edu
Keywords: immunotherapy, oncology, artificial intelligence, radiomics; lactate, dehydrogenase, PET, MRI, CT, SPECT
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About Oncotarget:
Oncotarget (a primarily oncology-focused, peer-reviewed, open access journal) aims to maximize research impact through insightful peer-review; eliminate borders between specialties by linking different fields of oncology, cancer research and biomedical sciences; and foster application of basic and clinical science.
Oncotarget is indexed and archived by PubMed/Medline, PubMed Central, Scopus, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).
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Journal
Oncotarget
Method of Research
Commentary/editorial
Subject of Research
Not applicable
Article Title
Artificial intelligence: A transformative tool in precision oncology
Article Publication Date
26-Aug-2024
COI Statement
Authors have no conflicts of interest to declare.
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