Generative AI in Cancer Imaging: Revolutionizing Detection & Diagnosis

“This editorial explores its impact on expanding datasets, improving image quality, and enabling predictive oncology.”

BUFFALO, NY- September 6, 2024 – A new editorial was published in Oncotarget's Volume 15 on September 4, 2024, entitled, “Generative AI in oncological imaging: Revolutionizing cancer detection and diagnosis.”

Generative AI is revolutionizing oncological imaging, enhancing cancer detection and diagnosis. This editorial explores its impact on expanding datasets, improving image quality, and advancing predictive oncology.

In their editorial, researchers Yashbir Singh, Quincy A. Hathaway and Bradley J. Erickson from the Department of Radiology, Mayo Clinic, in Rochester, Minnesota, discuss ethical considerations and offer a unique perspective on personalized cancer screening using AI-generated digital twins.

“As we navigate this exciting frontier, we must remain committed to ethical innovation, always keeping the patient at the center of our efforts.”

Generative AI is poised to revolutionize oncological imaging, offering new hope in the fight against cancer. And while challenges remain, generative AI in oncological imaging offers unprecedented opportunities to advance cancer care and improve patient outcomes.

Continue reading: DOI: https://doi.org/10.18632/oncotarget.28640

Correspondence to: Yashbir Singh - singh.yashbir@mayo.edu

Keywords: cancer, generative AI, oncological imaging, personalized cancer screening

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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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