Dunnmon JA - Search Results

1

Comparison of segmentation-free and segmentation-dependent computer-aided diagnosis of breast masses on a public mammography dataset.

Sawyer Lee R, Dunnmon JA, He A, Tang S, Ré C, Rubin DL. Sawyer Lee R, et al. Among authors: dunnmon ja. J Biomed Inform. 2021 Jan;113:103656. doi: 10.1016/j.jbi.2020.103656. Epub 2020 Dec 11. J Biomed Inform. 2021. PMID: 33309994 Free PMC article.

2

Learning to Compose Domain-Specific Transformations for Data Augmentation.

Ratner AJ, Ehrenberg HR, Hussain Z, Dunnmon J, Ré C. Ratner AJ, et al. Adv Neural Inf Process Syst. 2017 Dec;30:3239-3249. Adv Neural Inf Process Syst. 2017. PMID: 29375240 Free PMC article.

3

Assessment of Convolutional Neural Networks for Automated Classification of Chest Radiographs.

Dunnmon JA, Yi D, Langlotz CP, Ré C, Rubin DL, Lungren MP. Dunnmon JA, et al. Radiology. 2019 Feb;290(2):537-544. doi: 10.1148/radiol.2018181422. Epub 2018 Nov 13. Radiology. 2019. PMID: 30422093 Free PMC article.

4

Snorkel MeTaL: Weak Supervision for Multi-Task Learning.

Ratner A, Hancock B, Dunnmon J, Goldman R, Ré C. Ratner A, et al. Proc Second Workshop Data Manag End End Mach Learn (2018). 2018 Jun;2018:3. doi: 10.1145/3209889.3209898. Proc Second Workshop Data Manag End End Mach Learn (2018). 2018. PMID: 30931438 Free PMC article.

5

Weakly supervised classification of aortic valve malformations using unlabeled cardiac MRI sequences.

Fries JA, Varma P, Chen VS, Xiao K, Tejeda H, Saha P, Dunnmon J, Chubb H, Maskatia S, Fiterau M, Delp S, Ashley E, Ré C, Priest JR. Fries JA, et al. Among authors: dunnmon j. Nat Commun. 2019 Jul 15;10(1):3111. doi: 10.1038/s41467-019-11012-3. Nat Commun. 2019. PMID: 31308376 Free PMC article.

6

Training Complex Models with Multi-Task Weak Supervision.

Ratner A, Hancock B, Dunnmon J, Sala F, Pandey S, Ré C. Ratner A, et al. Proc AAAI Conf Artif Intell. 2019 Jan-Feb;33:4763-4771. doi: 10.1609/aaai.v33i01.33014763. Proc AAAI Conf Artif Intell. 2019. PMID: 31565535 Free PMC article.

7

Weak supervision as an efficient approach for automated seizure detection in electroencephalography.

Saab K, Dunnmon J, Ré C, Rubin D, Lee-Messer C. Saab K, et al. NPJ Digit Med. 2020 Apr 20;3:59. doi: 10.1038/s41746-020-0264-0. eCollection 2020. NPJ Digit Med. 2020. PMID: 32352037 Free PMC article.

8

Cross-Modal Data Programming Enables Rapid Medical Machine Learning.

Dunnmon JA, Ratner AJ, Saab K, Khandwala N, Markert M, Sagreiya H, Goldman R, Lee-Messer C, Lungren MP, Rubin DL, Ré C. Dunnmon JA, et al. Patterns (N Y). 2020 May 8;1(2):100019. doi: 10.1016/j.patter.2020.100019. Epub 2020 Apr 28. Patterns (N Y). 2020. PMID: 32776018 Free PMC article.

9

Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging.

Oakden-Rayner L, Dunnmon J, Carneiro G, Ré C. Oakden-Rayner L, et al. Proc ACM Conf Health Inference Learn (2020). 2020 Apr;2020:151-159. doi: 10.1145/3368555.3384468. Proc ACM Conf Health Inference Learn (2020). 2020. PMID: 33196064 Free PMC article.

10

[No title available]

[No authors listed] [No authors listed] PMID: 33597644

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