TY - JOUR

T1 - Artificial Intelligence and Early Detection of Pancreatic Cancer

T2 - 2020 Summative Review

AU - Kenner, Barbara

AU - Chari, Suresh T

AU - Kelsen, David

AU - Klimstra, David S

AU - Pandol, Stephen J

AU - Rosenthal, Michael

AU - Rustgi, Anil K

AU - Taylor, James A

AU - Yala, Adam

AU - Abul-Husn, Noura

AU - Andersen, Dana K

AU - Bernstein, David

AU - Brunak, Søren

AU - Canto, Marcia Irene

AU - Eldar, Yonina C

AU - Fishman, Elliot K

AU - Fleshman, Julie

AU - Go, Vay Liang W

AU - Holt, Jane M

AU - Field, Bruce

AU - Goldberg, Ann

AU - Hoos, William

AU - Iacobuzio-Donahue, Christine

AU - Li, Debiao

AU - Lidgard, Graham

AU - Maitra, Anirban

AU - Matrisian, Lynn M

AU - Poblete, Sung

AU - Rothschild, Laura

AU - Sander, Chris

AU - Schwartz, Lawrence H

AU - Shalit, Uri

AU - Srivastava, Sudhir

AU - Wolpin, Brian

PY - 2021

Y1 - 2021

N2 - ABSTRACT: Despite considerable research efforts, pancreatic cancer is associated with a dire prognosis and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly nonspecific. The premise of improved survival through early detection is that more individuals will benefit from potentially curative treatment. Artificial intelligence (AI) methodology has emerged as a successful tool for risk stratification and identification in general health care. In response to the maturity of AI, Kenner Family Research Fund conducted the 2020 AI and Early Detection of Pancreatic Cancer Virtual Summit (www.pdac-virtualsummit.org) in conjunction with the American Pancreatic Association, with a focus on the potential of AI to advance early detection efforts in this disease. This comprehensive presummit article was prepared based on information provided by each of the interdisciplinary participants on one of the 5 following topics: Progress, Problems, and Prospects for Early Detection; AI and Machine Learning; AI and Pancreatic Cancer-Current Efforts; Collaborative Opportunities; and Moving Forward-Reflections from Government, Industry, and Advocacy. The outcome from the robust Summit conversations, to be presented in a future white paper, indicate that significant progress must be the result of strategic collaboration among investigators and institutions from multidisciplinary backgrounds, supported by committed funders.

AB - ABSTRACT: Despite considerable research efforts, pancreatic cancer is associated with a dire prognosis and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly nonspecific. The premise of improved survival through early detection is that more individuals will benefit from potentially curative treatment. Artificial intelligence (AI) methodology has emerged as a successful tool for risk stratification and identification in general health care. In response to the maturity of AI, Kenner Family Research Fund conducted the 2020 AI and Early Detection of Pancreatic Cancer Virtual Summit (www.pdac-virtualsummit.org) in conjunction with the American Pancreatic Association, with a focus on the potential of AI to advance early detection efforts in this disease. This comprehensive presummit article was prepared based on information provided by each of the interdisciplinary participants on one of the 5 following topics: Progress, Problems, and Prospects for Early Detection; AI and Machine Learning; AI and Pancreatic Cancer-Current Efforts; Collaborative Opportunities; and Moving Forward-Reflections from Government, Industry, and Advocacy. The outcome from the robust Summit conversations, to be presented in a future white paper, indicate that significant progress must be the result of strategic collaboration among investigators and institutions from multidisciplinary backgrounds, supported by committed funders.

U2 - 10.1097/MPA.0000000000001762

DO - 10.1097/MPA.0000000000001762

M3 - Journal article

C2 - 33835956

VL - 50

SP - 251

EP - 279

JO - Pancreas

JF - Pancreas

SN - 0885-3177

IS - 3

ER -