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David Ohlssen

Showing results (11-20 of 18) with videos related to

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Biometrical Journal. Biometrische Zeitschrift|November 27, 2022
Comparing algorithms for characterizing treatment effect heterogeneity in randomized trialsSophie Sun, Konstantinos Sechidis, Yao Chen, et al.
Pharmaceutical Statistics|February 8, 2024
Predicting subgroup treatment effects for a new study: Motivations, results and learnings from running a data challenge in a pharmaceutical corporationBjörn Bornkamp, Silvia Zaoli, Michela Azzarito, et al.
Plos One|July 6, 2023
A deep learning approach to private data sharing of medical images using conditional generative adversarial networks (GANs)Hanxi Sun, Jason Plawinski, Sajanth Subramaniam, et al.
Human Brain Mapping|August 8, 2007
Components of variance in a multicentre functional MRI study and implications for calculation of statistical powerJohn Suckling, David Ohlssen, Christopher Andrew, et al.
Pharmaceutical Statistics|December 27, 2024
WATCH: A Workflow to Assess Treatment Effect Heterogeneity in Drug Development for Clinical Trial SponsorsKonstantinos Sechidis, Sophie Sun, Yao Chen, et al.
Pharmaceutical Statistics|September 17, 2013
Guidance on the implementation and reporting of a drug safety Bayesian network meta-analysisDavid Ohlssen, Karen L Price, H Amy Xia, et al.
Journal of Biomedical Informatics|April 20, 2024
A framework for longitudinal latent factor modelling of treatment response in clinical trials with applications to Psoriatic Arthritis and Rheumatoid ArthritisFabian Falck, Xuan Zhu, Sahra Ghalebikesabi, et al.
Clinical Pharmacology and Therapeutics|November 15, 2023
Methodology for Good Machine Learning with Multi-Omics DataThibaud Coroller, Berkman Sahiner, Anup Amatya, et al.
Pageof 2

Showing results (11-20 of 18) with videos related to

Sort By:
Pageof 2
You have reached the last page of results.This site can display upto 18 results.
Biometrical Journal. Biometrische Zeitschrift|November 27, 2022
Comparing algorithms for characterizing treatment effect heterogeneity in randomized trialsSophie Sun, Konstantinos Sechidis, Yao Chen, et al.
Pharmaceutical Statistics|February 8, 2024
Predicting subgroup treatment effects for a new study: Motivations, results and learnings from running a data challenge in a pharmaceutical corporationBjörn Bornkamp, Silvia Zaoli, Michela Azzarito, et al.
Plos One|July 6, 2023
A deep learning approach to private data sharing of medical images using conditional generative adversarial networks (GANs)Hanxi Sun, Jason Plawinski, Sajanth Subramaniam, et al.
Human Brain Mapping|August 8, 2007
Components of variance in a multicentre functional MRI study and implications for calculation of statistical powerJohn Suckling, David Ohlssen, Christopher Andrew, et al.
Pharmaceutical Statistics|December 27, 2024
WATCH: A Workflow to Assess Treatment Effect Heterogeneity in Drug Development for Clinical Trial SponsorsKonstantinos Sechidis, Sophie Sun, Yao Chen, et al.
Pharmaceutical Statistics|September 17, 2013
Guidance on the implementation and reporting of a drug safety Bayesian network meta-analysisDavid Ohlssen, Karen L Price, H Amy Xia, et al.
Journal of Biomedical Informatics|April 20, 2024
A framework for longitudinal latent factor modelling of treatment response in clinical trials with applications to Psoriatic Arthritis and Rheumatoid ArthritisFabian Falck, Xuan Zhu, Sahra Ghalebikesabi, et al.
Clinical Pharmacology and Therapeutics|November 15, 2023
Methodology for Good Machine Learning with Multi-Omics DataThibaud Coroller, Berkman Sahiner, Anup Amatya, et al.
Pageof 2