Browsing by author "Lee, Christoph I"
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Artificial Intelligence (AI) for the early detection of breast cancer: a scoping review to assess AI’s potential for screening practice.
Houssami, Nehmat; Kirkpatric-Jones, Georgia; Noguchi, Naomi; Lee, Christoph IPublished 2019Various factors are driving interest in the application of artificial intelligence (AI) for breast cancer (BC) detection, but it is unclear whether the evidence warrants large-scale use in population-based screening. We ...Article -
Artificial intelligence (AI) to enhance breast cancer screening: protocol for population-based cohort study of cancer detection
Marinovich, M Luke; Wylie, Elizabeth Jane; Lotter, William; Pearce, Alison; Carter, Stacy M; Lund, Helen; Waddell, Andrew; Kim, Jiye G; Pereira, Gavin F; Lee, Christoph I; Zackrisson, Sophia; Brennan, Meagan; Houssami, NehmatPublished 2022Introduction Artificial intelligence (AI) algorithms for interpreting mammograms have the potential to improve the effectiveness of population breast cancer screening programmes if they can detect cancers, including interval ...Article -
Artificial intelligence for breast cancer screening: Opportunity or hype?
Houssami, Nehmat; Lee, Christoph I; Buist, Diana S.M; Tao, DachengPublished 2017Interpretation of mammography for breast cancer (BC) screening can confer a mortality benefit through early BC detection, can miss a cancer that is present or fast growing, or can result in false-positives. Efforts to ...Article -
The impact of legislation mandating breast density notification – Review of the evidence
Houssami, Nehmat; Lee, Christoph IPublished 2018Breast density (BD) is an independent risk factor for breast cancer and reduces the sensitivity of mammography. The enactment of BD legislation in a majority of states in the USA mandating notification of risks associated ...Article -
Independent External Validation of Artificial Intelligence Algorithms for Automated Interpretation of Screening Mammography: A Systematic Review
Anderson, Anna W; Marinovich, M Luke; Houssami, Nehmat; Lowry, Kathryn P; Elmore, Joann G; Buist, Diana S M; Hofvind, Solveig; Lee, Christoph IPublished 2022Purpose: The aim of this study was to describe the current state of science regarding independent external validation of artificial intelligence (AI) technologies for screening mammography. Methods: A systematic review ...Article -
Interval and Subsequent Round Breast Cancer in a Randomized Controlled Trial Comparing Digital Breast Tomosynthesis and Digital Mammography Screening
Hofvind, Solveig; Moshina, Nataliia; Holen, Åsne S.; Danielsen, Anders S; Lee, Christoph I; Houssami, Nehmat; Aase, Hildegunn S; Akslen, Lars A; Haldorsen, Ingfrid SPublished 2021Prevalent digital breast tomosynthesis (DBT) has shown higher cancer detection rates and lower recall rates compared with those of digital mammography (DM). However, data are limited on rates and histopathologic tumor ...Article -
Pathways to breast cancer screening artificial intelligence algorithm validation
Lee, Christoph I; Houssami, Nehmat; Elmore, Joann G; Buist, Diana S.MPublished 2020As more artificial intelligence (AI)-enhanced mammography screening tools enter the clinical market, greater focus will be placed on external validation in diverse patient populations. In this viewpoint, we outline lessons ...Open AccessArticle
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