Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Matthew B. A. McDermott"'
Autor:
Laleh Seyyed-Kalantari, Haoran Zhang, Matthew B. A. McDermott, Irene Y. Chen, Marzyeh Ghassemi
Publikováno v:
Nature Medicine. 27:2176-2182
Artificial intelligence (AI) systems have increasingly achieved expert-level performance in medical imaging applications. However, there is growing concern that such AI systems may reflect and amplify human bias, and reduce the quality of their perfo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c359017cfba35fca0df025fa5149473a
https://doi.org/10.1038/s41591-021-01595-0
https://doi.org/10.1038/s41591-021-01595-0
Autor:
Jennifer P. Wang, Steven D. Sheridan, Isaac S. Kohane, Matthew B. A. McDermott, Peter Szolovits, Stephen J. Haggarty, Roy H. Perlis, Wen-Ning Zhao
Publikováno v:
IEEE/ACM Trans Comput Biol Bioinform
Gene expression data can offer deep, physiological insights beyond the static coding of the genome alone. We believe that realizing this potential requires specialized, high-capacity machine learning methods capable of using underlying biological str
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::93005d5d878b1714d12e4c14b887d19a
https://doi.org/10.1109/tcbb.2019.2910061
https://doi.org/10.1109/tcbb.2019.2910061
Autor:
Laleh Seyyed-Kalantari, Haoran Zhang, Matthew B. A. McDermott, Irene Y. Chen, Marzyeh Ghassemi
Publikováno v:
Nature Medicine. 28:1161-1162
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6eba531bfb1d185ea67e1c47a4afe3c2
https://doi.org/10.1038/s41591-022-01854-8
https://doi.org/10.1038/s41591-022-01854-8
Autor:
Anna Goldenberg, Wancong Zhang, Matthew B. A. McDermott, Marzyeh Ghassemi, Peter Szolovits, Evan Kim, Bret Nestor
Publikováno v:
CHIL
Pre-training (PT) has been used successfully in many areas of machine learning. One area where PT would be extremely impactful is over electronic health record (EHR) data. Successful PT strategies on this modality could improve model performance in d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f4d0bc8652d6890273ac1550075508d7
https://doi.org/10.1145/3450439.3451877
https://doi.org/10.1145/3450439.3451877
Autor:
Nikki Marinsek, Matthew B. A. McDermott, Rajesh Ranganath, Luca Foschini, Marzyeh Ghassemi, Shirly Wang
Publikováno v:
Science Translational Medicine. 13
Machine learning for health must be reproducible to ensure reliable clinical use. We evaluated 511 scientific papers across several machine learning subfields and found that machine learning for health compared poorly to other areas regarding reprodu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6405bf2c9fb5b9809a5ab4821be4377e
https://doi.org/10.1126/scitranslmed.abb1655
https://doi.org/10.1126/scitranslmed.abb1655
Autor:
Samuel G, Finlayson, Matthew B A, McDermott, Alex V, Pickering, Scott L, Lipnick, Isaac S, Kohane
Publikováno v:
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Modeling the relationship between chemical structure and molecular activity is a key goal in drug development. Many benchmark tasks have been proposed for molecular property prediction, but these tasks are generally aimed at specific, isolated biomed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::25faa9cfd511a4f6d25b0a2b1039418e
https://pubmed.ncbi.nlm.nih.gov/33691024
https://pubmed.ncbi.nlm.nih.gov/33691024
Autor:
Marzyeh Ghassemi, Guanxiong Liu, Matthew B. A. McDermott, Laleh Seyyed-Kalantari, Irene Y. Chen
Publikováno v:
PSB
Machine learning systems have received much attention recently for their ability to achieve expert-level performance on clinical tasks, particularly in medical imaging. Here, we examine the extent to which state-of-the-art deep learning classifiers t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97d92812a5c71d1e3120ca296be15e7a
https://pubmed.ncbi.nlm.nih.gov/33691020
https://pubmed.ncbi.nlm.nih.gov/33691020
Publikováno v:
CHIL
In this work, we examine the extent to which embeddings may encode marginalized populations differently, and how this may lead to a perpetuation of biases and worsened performance on clinical tasks. We pretrain deep embedding models (BERT) on medical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::18d7013ebfd2c8f24e4751a978a54bff
http://arxiv.org/abs/2003.11515
http://arxiv.org/abs/2003.11515
Autor:
Eliot C Bush, Anne E Clark, Chris M DeBoever, Lillian E Haynes, Sidra Hussain, Singer Ma, Matthew B A McDermott, Adam M Novak, John S Wentworth
Publikováno v:
PLoS ONE, Vol 7, Iss 11, p e48920 (2012)
A significant proportion of enzymes display cooperativity in binding ligand molecules, and such effects have an important impact on metabolic regulation. This is easiest to understand in the case of positive cooperativity. Sharp responses to changes
Externí odkaz:
https://doaj.org/article/3df89597721a4945b0d687097cb52598
Autor:
Isaac S. Kohane, Samuel G. Finlayson, Scott Lipnick, Alex V. Pickering, Matthew B. A. McDermott
Publikováno v:
PSB
Modeling the relationship between chemical structure and molecular activity is a key goal in drug development. Many benchmark tasks have been proposed for molecular property prediction, but these tasks are generally aimed at specific, isolated biomed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::777f153928c64a26b1fb05467ab61fb9
http://arxiv.org/abs/1911.10241
http://arxiv.org/abs/1911.10241