Oakden-Rayner L - Search Results

1

Stroke prognostication for discharge planning with machine learning: A derivation study.

Bacchi S, Oakden-Rayner L, Menon DK, Jannes J, Kleinig T, Koblar S. Bacchi S, et al. J Clin Neurosci. 2020 Sep;79:100-103. doi: 10.1016/j.jocn.2020.07.046. Epub 2020 Aug 5. J Clin Neurosci. 2020. PMID: 33070874

2

Deep Learning Natural Language Processing Successfully Predicts the Cerebrovascular Cause of Transient Ischemic Attack-Like Presentations.

Bacchi S, Oakden-Rayner L, Zerner T, Kleinig T, Patel S, Jannes J. Bacchi S, et al. Stroke. 2019 Mar;50(3):758-760. doi: 10.1161/STROKEAHA.118.024124. Stroke. 2019. PMID: 30653397

3

Deep Learning in the Prediction of Ischaemic Stroke Thrombolysis Functional Outcomes: A Pilot Study.

Bacchi S, Zerner T, Oakden-Rayner L, Kleinig T, Patel S, Jannes J. Bacchi S, et al. Acad Radiol. 2020 Feb;27(2):e19-e23. doi: 10.1016/j.acra.2019.03.015. Epub 2019 Apr 30. Acad Radiol. 2020. PMID: 31053480

4

Deep learning in the detection of high-grade glioma recurrence using multiple MRI sequences: A pilot study.

Bacchi S, Zerner T, Dongas J, Asahina AT, Abou-Hamden A, Otto S, Oakden-Rayner L, Patel S. Bacchi S, et al. J Clin Neurosci. 2019 Dec;70:11-13. doi: 10.1016/j.jocn.2019.10.003. Epub 2019 Oct 21. J Clin Neurosci. 2019. PMID: 31648967

5

Machine learning in the prediction of medical inpatient length of stay.

Bacchi S, Tan Y, Oakden-Rayner L, Jannes J, Kleinig T, Koblar S. Bacchi S, et al. Intern Med J. 2022 Feb;52(2):176-185. doi: 10.1111/imj.14962. Epub 2021 Oct 27. Intern Med J. 2022. PMID: 33094899 Review.

6

Prospective and external validation of stroke discharge planning machine learning models.

Bacchi S, Oakden-Rayner L, Menon DK, Moey A, Jannes J, Kleinig T, Koblar S. Bacchi S, et al. J Clin Neurosci. 2022 Feb;96:80-84. doi: 10.1016/j.jocn.2021.12.031. Epub 2022 Jan 6. J Clin Neurosci. 2022. PMID: 34999495

7

Medical student knowledge and critical appraisal of machine learning: a multicentre international cross-sectional study.

Blacketer C, Parnis R, B Franke K, Wagner M, Wang D, Tan Y, Oakden-Rayner L, Gallagher S, Perry SW, Licinio J, Symonds I, Thomas J, Duggan P, Bacchi S. Blacketer C, et al. Intern Med J. 2021 Sep;51(9):1539-1542. doi: 10.1111/imj.15479. Intern Med J. 2021. PMID: 34541769

8

Chest radiographs and machine learning - Past, present and future.

Jones CM, Buchlak QD, Oakden-Rayner L, Milne M, Seah J, Esmaili N, Hachey B. Jones CM, et al. J Med Imaging Radiat Oncol. 2021 Aug;65(5):538-544. doi: 10.1111/1754-9485.13274. Epub 2021 Jun 25. J Med Imaging Radiat Oncol. 2021. PMID: 34169648 Free PMC article. Review.

9

Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study.

Seah JCY, Tang CHM, Buchlak QD, Holt XG, Wardman JB, Aimoldin A, Esmaili N, Ahmad H, Pham H, Lambert JF, Hachey B, Hogg SJF, Johnston BP, Bennett C, Oakden-Rayner L, Brotchie P, Jones CM. Seah JCY, et al. Lancet Digit Health. 2021 Aug;3(8):e496-e506. doi: 10.1016/S2589-7500(21)00106-0. Epub 2021 Jul 1. Lancet Digit Health. 2021. PMID: 34219054 Free article.

10

Do comprehensive deep learning algorithms suffer from hidden stratification? A retrospective study on pneumothorax detection in chest radiography.

Seah J, Tang C, Buchlak QD, Milne MR, Holt X, Ahmad H, Lambert J, Esmaili N, Oakden-Rayner L, Brotchie P, Jones CM. Seah J, et al. BMJ Open. 2021 Dec 7;11(12):e053024. doi: 10.1136/bmjopen-2021-053024. BMJ Open. 2021. PMID: 34876430 Free PMC article.

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