TY - JOUR
T1 - Cancer Informatics for Cancer Centers
T2 - Sharing Ideas on How to Build an Artificial Intelligence-Ready Informatics Ecosystem for Radiation Oncology
AU - Bitterman, Danielle S
AU - Gensheimer, Michael F
AU - Jaffray, David
AU - Pryma, Daniel A
AU - Jiang, Steve B
AU - Morin, Olivier
AU - Ginart, Jorge Barrios
AU - Upadhaya, Taman
AU - Vallis, Katherine A
AU - Buatti, John M
AU - Deasy, Joseph
AU - Hsiao, H Timothy
AU - Chung, Caroline
AU - Fuller, Clifton D
AU - Greenspan, Emily
AU - Cloyd-Warwick, Kristy
AU - Courdy, Samir
AU - Mao, Allen
AU - Barnholtz-Sloan, Jill
AU - Topaloglu, Umit
AU - Hands, Isaac
AU - Maurer, Ian
AU - Terry, May
AU - Curran, Walter J
AU - Le, Quynh-Thu
AU - Nadaf, Sorena
AU - Kibbe, Warren
PY - 2023/9
Y1 - 2023/9
N2 - In August 2022, the Cancer Informatics for Cancer Centers brought together cancer informatics leaders for its biannual symposium, Precision Medicine Applications in Radiation Oncology, co-chaired by Quynh-Thu Le, MD (Stanford University), and Walter J. Curran, MD (GenesisCare). Over the course of 3 days, presenters discussed a range of topics relevant to radiation oncology and the cancer informatics community more broadly, including biomarker development, decision support algorithms, novel imaging tools, theranostics, and artificial intelligence (AI) for the radiotherapy workflow. Since the symposium, there has been an impressive shift in the promise and potential for integration of AI in clinical care, accelerated in large part by major advances in generative AI. AI is now poised more than ever to revolutionize cancer care. Radiation oncology is a field that uses and generates a large amount of digital data and is therefore likely to be one of the first fields to be transformed by AI. As experts in the collection, management, and analysis of these data, the informatics community will take a leading role in ensuring that radiation oncology is prepared to take full advantage of these technological advances. In this report, we provide highlights from the symposium, which took place in Santa Barbara, California, from August 29 to 31, 2022. We discuss lessons learned from the symposium for data acquisition, management, representation, and sharing, and put these themes into context to prepare radiation oncology for the successful and safe integration of AI and informatics technologies.
AB - In August 2022, the Cancer Informatics for Cancer Centers brought together cancer informatics leaders for its biannual symposium, Precision Medicine Applications in Radiation Oncology, co-chaired by Quynh-Thu Le, MD (Stanford University), and Walter J. Curran, MD (GenesisCare). Over the course of 3 days, presenters discussed a range of topics relevant to radiation oncology and the cancer informatics community more broadly, including biomarker development, decision support algorithms, novel imaging tools, theranostics, and artificial intelligence (AI) for the radiotherapy workflow. Since the symposium, there has been an impressive shift in the promise and potential for integration of AI in clinical care, accelerated in large part by major advances in generative AI. AI is now poised more than ever to revolutionize cancer care. Radiation oncology is a field that uses and generates a large amount of digital data and is therefore likely to be one of the first fields to be transformed by AI. As experts in the collection, management, and analysis of these data, the informatics community will take a leading role in ensuring that radiation oncology is prepared to take full advantage of these technological advances. In this report, we provide highlights from the symposium, which took place in Santa Barbara, California, from August 29 to 31, 2022. We discuss lessons learned from the symposium for data acquisition, management, representation, and sharing, and put these themes into context to prepare radiation oncology for the successful and safe integration of AI and informatics technologies.
U2 - 10.1200/CCI.23.00136
DO - 10.1200/CCI.23.00136
M3 - Article
C2 - 38055914
SN - 2473-4276
VL - 7
SP - e2300136
JO - JCO clinical cancer informatics
JF - JCO clinical cancer informatics
ER -
