3 citations · 8 across the 7 of their papers we have counts for
8 papers
Prediction of Survival Outcomes under Clinical Presence Shift: A Joint Neural Network Architecture
Vincent Jeanselme, Glen Martin, Matthew Sperrin +3
Electronic health records arise from the complex interaction between patients and the healthcare system. This observation process of interactions, referred to as clinical presence,…
Competing Risks: Impact on Risk Estimation and Algorithmic Fairness
Vincent Jeanselme, Brian Tom, Jessica Barrett
Accurate time-to-event prediction is integral to decision-making, informing medical guidelines, hiring decisions, and resource allocation. Survival analysis, the quantitative frame…
Identifying treatment response subgroups in observational time-to-event data
Vincent Jeanselme, Chang Ho Yoon, Fabian Falck +2
Identifying patient subgroups with different treatment responses is an important task to inform medical recommendations, guidelines, and the design of future clinical trials. Exist…
Exploring the big data paradox for various estimands using vaccination data from the global COVID-19 Trends and Impact Survey (CTIS)
Youqi Yang, Walter Dempsey, Peisong Han +4
Selection bias poses a challenge to statistical inference validity in non-probability surveys. This study compared estimates of the first-dose COVID-19 vaccination rates among Indi…
Neural Fine-Gray: Monotonic neural networks for competing risks
Vincent Jeanselme, Chang Ho Yoon, Brian Tom +1
Time-to-event modelling, known as survival analysis, differs from standard regression as it addresses censoring in patients who do not experience the event of interest. Despite com…
Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness
Vincent Jeanselme, Maria De-Arteaga, Zhe Zhang +2
Machine learning risks reinforcing biases present in data and, as we argue in this work, in what is absent from data. In healthcare, societal and decision biases shape patterns in…
DeepJoint: Robust Survival Modelling Under Clinical Presence Shift
Vincent Jeanselme, Glen Martin, Niels Peek +3
Observational data in medicine arise as a result of the complex interaction between patients and the healthcare system. The sampling process is often highly irregular and itself co…
Latent class mixed modelling for phenotypic stratification of primary biliary cholangitis patients on first line treatment
Victoria Mulcahy, Anais Rouanet, Alessio Gerussi +5
In patients with primary biliary cholangitis (PBC), the serum liver biochemistry measured during treatment with ursodeoxycholic acid (the UDCA response) accurately predicts long-te…