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Items: 6

1.

Adversarial attacks on medical machine learning.

Finlayson SG, Bowers JD, Ito J, Zittrain JL, Beam AL, Kohane IS.

Science. 2019 Mar 22;363(6433):1287-1289. doi: 10.1126/science.aaw4399. No abstract available.

PMID:
30898923
2.

Systemic nature of spinal muscular atrophy revealed by studying insurance claims.

Lipnick SL, Agniel DM, Aggarwal R, Makhortova NR, Finlayson SG, Brocato A, Palmer N, Darras BT, Kohane I, Rubin LL.

PLoS One. 2019 Mar 14;14(3):e0213680. doi: 10.1371/journal.pone.0213680. eCollection 2019.

3.

Automatic Categorization and Scoring of Solid, Part-Solid and Non-Solid Pulmonary Nodules in CT Images with Convolutional Neural Network.

Tu X, Xie M, Gao J, Ma Z, Chen D, Wang Q, Finlayson SG, Ou Y, Cheng JZ.

Sci Rep. 2017 Sep 1;7(1):8533. doi: 10.1038/s41598-017-08040-8.

4.

Toward rapid learning in cancer treatment selection: An analytical engine for practice-based clinical data.

Finlayson SG, Levy M, Reddy S, Rubin DL.

J Biomed Inform. 2016 Apr;60:104-13. doi: 10.1016/j.jbi.2016.01.005. Epub 2016 Feb 2.

5.

Detecting unplanned care from clinician notes in electronic health records.

Tamang S, Patel MI, Blayney DW, Kuznetsov J, Finlayson SG, Vetteth Y, Shah N.

J Oncol Pract. 2015 May;11(3):e313-9. doi: 10.1200/JOP.2014.002741.

6.

Building the graph of medicine from millions of clinical narratives.

Finlayson SG, LePendu P, Shah NH.

Sci Data. 2014 Sep 16;1:140032. doi: 10.1038/sdata.2014.32. eCollection 2014.

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