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pro vyhledávání: '"Liley, James"'
Clinical prediction models are statistical or machine learning models used to quantify the risk of a certain health outcome using patient data. These can then inform potential interventions on patients, causing an effect called performative predictio
Externí odkaz:
http://arxiv.org/abs/2406.03161
Autor:
Smith, Jim, Preen, Richard J., McCarthy, Andrew, Albashir, Maha, Crespi-Boixader, Alba, Mumtaz, Shahzad, Liley, James, Rogers, Simon, Jones, Yola
We present SACRO-ML, an integrated suite of open source Python tools to facilitate the statistical disclosure control (SDC) of machine learning (ML) models trained on confidential data prior to public release. SACRO-ML combines (i) a SafeModel packag
Externí odkaz:
http://arxiv.org/abs/2212.01233
Autor:
Jefferson, Emily, Liley, James, Malone, Maeve, Reel, Smarti, Crespi-Boixader, Alba, Kerasidou, Xaroula, Tava, Francesco, McCarthy, Andrew, Preen, Richard, Blanco-Justicia, Alberto, Mansouri-Benssassi, Esma, Domingo-Ferrer, Josep, Beggs, Jillian, Chuter, Antony, Cole, Christian, Ritchie, Felix, Daly, Angela, Rogers, Simon, Smith, Jim
TREs are widely, and increasingly used to support statistical analysis of sensitive data across a range of sectors (e.g., health, police, tax and education) as they enable secure and transparent research whilst protecting data confidentiality. There
Externí odkaz:
http://arxiv.org/abs/2211.01656
In complex settings, such as healthcare, predictive risk scores play an increasingly crucial role in guiding interventions. However, directly updating risk scores used to guide intervention can lead to biased risk estimates. To address this, we propo
Externí odkaz:
http://arxiv.org/abs/2202.06374
Autor:
Liley, James
Predictive risk scores estimating probabilities for a binary outcome on the basis of observed covariates are common across the sciences. They are frequently developed with the intent of avoiding the outcome in question by intervening in response to e
Externí odkaz:
http://arxiv.org/abs/2110.04163
Autor:
Dudley, Robert, Dodgson, Guy, Common, Stephanie, Ogundimu, Emmanuel, Liley, James, O'Grady, Lucy, Watson, Florence, Gibbs, Christopher, Arnott, Bronia, Fernyhough, Charles, Alderson-Day, Ben, Aynsworth, Charlotte
Publikováno v:
In Journal of Psychiatric Research June 2024 174:289-296
Autor:
Liley, James, Emerson, Samuel R, Mateen, Bilal A, Vallejos, Catalina A, Aslett, Louis J M, Vollmer, Sebastian J
Machine learning is increasingly being used to generate prediction models for use in a number of real-world settings, from credit risk assessment to clinical decision support. Recent discussions have highlighted potential problems in the updating of
Externí odkaz:
http://arxiv.org/abs/2010.11530
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Autor:
Liley, James
High dimensional case control studies are ubiquitous in the biological sciences, particularly genomics. To maximise power while constraining cost and to minimise type-1 error rates, researchers typically seek to replicate findings in a second experim
Externí odkaz:
http://arxiv.org/abs/1702.02827