Cargando…

Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review

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 c...

Descripción completa

Detalles Bibliográficos
Autores principales: Kenner, Barbara, Chari, Suresh T., Kelsen, David, Klimstra, David S., Pandol, Stephen J., Rosenthal, Michael, Rustgi, Anil K., Taylor, James A., Yala, Adam, Abul-Husn, Noura, Andersen, Dana K., Bernstein, David, Brunak, Søren, Canto, Marcia Irene, Eldar, Yonina C., Fishman, Elliot K., Fleshman, Julie, Go, Vay Liang W., Holt, Jane M., Field, Bruce, Goldberg, Ann, Hoos, William, Iacobuzio-Donahue, Christine, Li, Debiao, Lidgard, Graham, Maitra, Anirban, Matrisian, Lynn M., Poblete, Sung, Rothschild, Laura, Sander, Chris, Schwartz, Lawrence H., Shalit, Uri, Srivastava, Sudhir, Wolpin, Brian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041569/
https://www.ncbi.nlm.nih.gov/pubmed/33835956
http://dx.doi.org/10.1097/MPA.0000000000001762
_version_ 1783677957879889920
author Kenner, Barbara
Chari, Suresh T.
Kelsen, David
Klimstra, David S.
Pandol, Stephen J.
Rosenthal, Michael
Rustgi, Anil K.
Taylor, James A.
Yala, Adam
Abul-Husn, Noura
Andersen, Dana K.
Bernstein, David
Brunak, Søren
Canto, Marcia Irene
Eldar, Yonina C.
Fishman, Elliot K.
Fleshman, Julie
Go, Vay Liang W.
Holt, Jane M.
Field, Bruce
Goldberg, Ann
Hoos, William
Iacobuzio-Donahue, Christine
Li, Debiao
Lidgard, Graham
Maitra, Anirban
Matrisian, Lynn M.
Poblete, Sung
Rothschild, Laura
Sander, Chris
Schwartz, Lawrence H.
Shalit, Uri
Srivastava, Sudhir
Wolpin, Brian
author_facet Kenner, Barbara
Chari, Suresh T.
Kelsen, David
Klimstra, David S.
Pandol, Stephen J.
Rosenthal, Michael
Rustgi, Anil K.
Taylor, James A.
Yala, Adam
Abul-Husn, Noura
Andersen, Dana K.
Bernstein, David
Brunak, Søren
Canto, Marcia Irene
Eldar, Yonina C.
Fishman, Elliot K.
Fleshman, Julie
Go, Vay Liang W.
Holt, Jane M.
Field, Bruce
Goldberg, Ann
Hoos, William
Iacobuzio-Donahue, Christine
Li, Debiao
Lidgard, Graham
Maitra, Anirban
Matrisian, Lynn M.
Poblete, Sung
Rothschild, Laura
Sander, Chris
Schwartz, Lawrence H.
Shalit, Uri
Srivastava, Sudhir
Wolpin, Brian
author_sort Kenner, Barbara
collection PubMed
description 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.
format Online
Article
Text
id pubmed-8041569
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Lippincott Williams & Wilkins
record_format MEDLINE/PubMed
spelling pubmed-80415692021-04-19 Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review Kenner, Barbara Chari, Suresh T. Kelsen, David Klimstra, David S. Pandol, Stephen J. Rosenthal, Michael Rustgi, Anil K. Taylor, James A. Yala, Adam Abul-Husn, Noura Andersen, Dana K. Bernstein, David Brunak, Søren Canto, Marcia Irene Eldar, Yonina C. Fishman, Elliot K. Fleshman, Julie Go, Vay Liang W. Holt, Jane M. Field, Bruce Goldberg, Ann Hoos, William Iacobuzio-Donahue, Christine Li, Debiao Lidgard, Graham Maitra, Anirban Matrisian, Lynn M. Poblete, Sung Rothschild, Laura Sander, Chris Schwartz, Lawrence H. Shalit, Uri Srivastava, Sudhir Wolpin, Brian Pancreas Conference Report 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. Lippincott Williams & Wilkins 2021-03 2021-04-08 /pmc/articles/PMC8041569/ /pubmed/33835956 http://dx.doi.org/10.1097/MPA.0000000000001762 Text en Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Conference Report
Kenner, Barbara
Chari, Suresh T.
Kelsen, David
Klimstra, David S.
Pandol, Stephen J.
Rosenthal, Michael
Rustgi, Anil K.
Taylor, James A.
Yala, Adam
Abul-Husn, Noura
Andersen, Dana K.
Bernstein, David
Brunak, Søren
Canto, Marcia Irene
Eldar, Yonina C.
Fishman, Elliot K.
Fleshman, Julie
Go, Vay Liang W.
Holt, Jane M.
Field, Bruce
Goldberg, Ann
Hoos, William
Iacobuzio-Donahue, Christine
Li, Debiao
Lidgard, Graham
Maitra, Anirban
Matrisian, Lynn M.
Poblete, Sung
Rothschild, Laura
Sander, Chris
Schwartz, Lawrence H.
Shalit, Uri
Srivastava, Sudhir
Wolpin, Brian
Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review
title Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review
title_full Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review
title_fullStr Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review
title_full_unstemmed Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review
title_short Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review
title_sort artificial intelligence and early detection of pancreatic cancer: 2020 summative review
topic Conference Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041569/
https://www.ncbi.nlm.nih.gov/pubmed/33835956
http://dx.doi.org/10.1097/MPA.0000000000001762
work_keys_str_mv AT kennerbarbara artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT charisuresht artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT kelsendavid artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT klimstradavids artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT pandolstephenj artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT rosenthalmichael artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT rustgianilk artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT taylorjamesa artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT yalaadam artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT abulhusnnoura artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT andersendanak artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT bernsteindavid artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT brunaksøren artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT cantomarciairene artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT eldaryoninac artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT fishmanelliotk artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT fleshmanjulie artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT govayliangw artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT holtjanem artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT fieldbruce artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT goldbergann artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT hooswilliam artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT iacobuziodonahuechristine artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT lidebiao artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT lidgardgraham artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT maitraanirban artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT matrisianlynnm artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT pobletesung artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT rothschildlaura artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT sanderchris artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT schwartzlawrenceh artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT shalituri artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT srivastavasudhir artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview
AT wolpinbrian artificialintelligenceandearlydetectionofpancreaticcancer2020summativereview