Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Benjamin J. Lengerich"'
Autor:
Benjamin D Lee, Anthony Gitter, Casey S Greene, Sebastian Raschka, Finlay Maguire, Alexander J Titus, Michael D Kessler, Alexandra J Lee, Marc G Chevrette, Paul Allen Stewart, Thiago Britto-Borges, Evan M Cofer, Kun-Hsing Yu, Juan Jose Carmona, Elana J Fertig, Alexandr A Kalinin, Brandon Signal, Benjamin J Lengerich, Timothy J Triche, Simina M Boca
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 3, p e1009803 (2022)
Externí odkaz:
https://doaj.org/article/c0cf492068b7496c8a19201d07339e91
Real-world evidence is confounded by treatments, so data-driven systems can learn to recapitulate biases that influenced treatment decisions. This confounding presents a challenge: uninterpretable black-box systems can put patients at risk by confusi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::39d42da506cca3d3dc25b01ffb08d23a
https://doi.org/10.1101/2022.04.30.22274520
https://doi.org/10.1101/2022.04.30.22274520
Publikováno v:
medRxiv
article-version (status) pre
article-version (number) 1
article-version (status) pre
article-version (number) 1
Treatment protocols, treatment availability, disease understanding, and viral characteristics have changed over the course of the Covid-19 pandemic; as a result, the risks associated with patient comorbidities and biomarkers have also changed. We add
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bbb0b0c9e45a78aa4c91d9e0d26c5455
http://europepmc.org/articles/PMC8687469
http://europepmc.org/articles/PMC8687469
Testing multiple treatments for heterogeneous (varying) effectiveness with respect to many underlying risk factors requires many pairwise tests; we would like to instead automatically discover and visualize patient archetypes and predictors of treatm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::54bf355f7951ef828ed9176c06da83cb
https://doi.org/10.1101/2021.10.30.21265430
https://doi.org/10.1101/2021.10.30.21265430
Publikováno v:
Journal of biomedical informatics. 130
Testing multiple treatments for heterogeneous (varying) effectiveness with respect to many underlying risk factors requires many pairwise tests; we would like to instead automatically discover and visualize patient archetypes and predictors of treatm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c12bf983fdf5b589f401e6620f7faa7
https://pubmed.ncbi.nlm.nih.gov/35504543
https://pubmed.ncbi.nlm.nih.gov/35504543
Autor:
Leora I. Horwitz, Alexander Peysakhovich, Rich Caruana, Benjamin J. Lengerich, Yin Aphinyanaphongs
Glucocorticoids have been shown to improve outcomes of patients with severe cases of Covid-19. However, criteria for prescribing glucocorticoids are currently limited. To identify potential for targeting, we perform an observational analysis of morta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c1c751367efe9c0dcb7c441c6028f022
https://doi.org/10.1101/2021.06.15.21251794
https://doi.org/10.1101/2021.06.15.21251794
Autor:
Benjamin D. Lee, Anthony Gitter, Casey S. Greene, Sebastian Raschka, Finlay Maguire, Alexander J. Titus, Michael D. Kessler, Alexandra J. Lee, Marc G. Chevrette, Paul Allen Stewart, Thiago Britto-Borges, Evan M. Cofer, Kun-Hsing Yu, Juan Jose Carmona, Elana J. Fertig, Alexandr A. Kalinin, Brandon Signal, Benjamin J. Lengerich, Timothy J. Triche, Simina M. Boca
Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling. A
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::69a4d6cab698ba20ff5552a5414b8c79
http://arxiv.org/abs/2105.14372
http://arxiv.org/abs/2105.14372
Autor:
Benjamin J. Lengerich, Sami Labbaki, Maruan Al-Shedivat, Jennifer Williams, Amir H. Alavi, Eric P. Xing
Summarizing multiple data modalities into a parsimonious cancer “subtype” is difficult because the most informative representation of each patient’s disease is not observed. We propose to model these latent summaries asdiscriminative subtypes:
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eeec042e21cde3397c0b42a06cc19de9
Publikováno v:
Bioinformatics
Motivation Association studies to discover links between genetic markers and phenotypes are central to bioinformatics. Methods of regularized regression, such as variants of the Lasso, are popular for this task. Despite the good predictive performanc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44a3edd4db7223d85004f3b809c23646
http://europepmc.org/articles/PMC6449749
http://europepmc.org/articles/PMC6449749
Autor:
Kristin Sitcov, William B. Weeks, Sydney Spencer, Colleen Daly, Vivienne Souter, Rich Caruana, Ian Painter, Benjamin J. Lengerich
Publikováno v:
American Journal of Obstetrics and Gynecology. 224:S629-S630
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5749e075c1cc9f2e85cf6accc84e146e
https://doi.org/10.1016/j.ajog.2020.12.1042
https://doi.org/10.1016/j.ajog.2020.12.1042