Hickman SE - Search Results

1

Deep Learning Algorithms for Breast Cancer Detection in a UK Screening Cohort: As Stand-alone Readers and Combined with Human Readers.

Hickman SE, Payne NR, Black RT, Huang Y, Priest AN, Hudson S, Kasmai B, Juette A, Nanaa M, Gilbert FJ. Hickman SE, et al. Radiology. 2024 Nov;313(2):e233147. doi: 10.1148/radiol.233147. Radiology. 2024. PMID: 39560480

2

Opportunities in cancer imaging: risk-adapted breast imaging in screening.

Gilbert FJ, Hickman SE, Baxter GC, Allajbeu I, James J, Caraco C, Vinnicombe S. Gilbert FJ, et al. Among authors: hickman se. Clin Radiol. 2021 Oct;76(10):763-773. doi: 10.1016/j.crad.2021.02.013. Epub 2021 Apr 2. Clin Radiol. 2021. PMID: 33820637 Review.

3

Machine Learning for Workflow Applications in Screening Mammography: Systematic Review and Meta-Analysis.

Hickman SE, Woitek R, Le EPV, Im YR, Mouritsen Luxhøj C, Aviles-Rivero AI, Baxter GC, MacKay JW, Gilbert FJ. Hickman SE, et al. Radiology. 2022 Jan;302(1):88-104. doi: 10.1148/radiol.2021210391. Epub 2021 Oct 19. Radiology. 2022. PMID: 34665034 Free PMC article.

4

Overview of trials on artificial intelligence algorithms in breast cancer screening - A roadmap for international evaluation and implementation.

van Nijnatten TJA, Payne NR, Hickman SE, Ashrafian H, Gilbert FJ. van Nijnatten TJA, et al. Among authors: hickman se. Eur J Radiol. 2023 Oct;167:111087. doi: 10.1016/j.ejrad.2023.111087. Epub 2023 Sep 8. Eur J Radiol. 2023. PMID: 37690352 Free article. Review.

5

Mammography Breast Cancer Screening Triage Using Deep Learning: A UK Retrospective Study.

Hickman SE, Payne NR, Black RT, Huang Y, Priest AN, Hudson S, Kasmai B, Juette A, Nanaa M, Aniq MI, Sienko A, Gilbert FJ. Hickman SE, et al. Radiology. 2023 Nov;309(2):e231173. doi: 10.1148/radiol.231173. Radiology. 2023. PMID: 37987665

6

Breast density effect on the sensitivity of digital screening mammography in a UK cohort.

Payne NR, Hickman SE, Black R, Priest AN, Hudson S, Gilbert FJ. Payne NR, et al. Among authors: hickman se. Eur Radiol. 2025 Jan;35(1):177-187. doi: 10.1007/s00330-024-10951-w. Epub 2024 Jul 17. Eur Radiol. 2025. PMID: 39017933 Free PMC article.

7

Accuracy of an Artificial Intelligence System for Interval Breast Cancer Detection at Screening Mammography.

Nanaa M, Gupta VO, Hickman SE, Allajbeu I, Payne NR, Arponen O, Black R, Huang Y, Priest AN, Gilbert FJ. Nanaa M, et al. Among authors: hickman se. Radiology. 2024 Aug;312(2):e232303. doi: 10.1148/radiol.232303. Radiology. 2024. PMID: 39189901

8

Artificial intelligence in breast imaging.

Le EPV, Wang Y, Huang Y, Hickman S, Gilbert FJ. Le EPV, et al. Clin Radiol. 2019 May;74(5):357-366. doi: 10.1016/j.crad.2019.02.006. Epub 2019 Mar 18. Clin Radiol. 2019. PMID: 30898381 Review.

9

Adoption of artificial intelligence in breast imaging: evaluation, ethical constraints and limitations.

Hickman SE, Baxter GC, Gilbert FJ. Hickman SE, et al. Br J Cancer. 2021 Jul;125(1):15-22. doi: 10.1038/s41416-021-01333-w. Epub 2021 Mar 26. Br J Cancer. 2021. PMID: 33772149 Free PMC article. Review.

10

Corrigendum to "Overview of trials on artificial intelligence algorithms in breast cancer screening - A roadmap for international evaluation and implementation" [Eur. J. Radiol. 167 (2023) 111087].

van Nijnatten TJA, Payne NR, Hickman SE, Ashrafian H, Gilbert FJ. van Nijnatten TJA, et al. Among authors: hickman se. Eur J Radiol. 2024 Jan;170:111202. doi: 10.1016/j.ejrad.2023.111202. Epub 2023 Nov 20. Eur J Radiol. 2024. PMID: 37988959 No abstract available.

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