The 44th Conference of the International Society for Clinical Biostatistics (ISCB44) will be taking place in Milan-Italy, at the University of Milano-Bicocca, on 27-31 August 2023.
The program will include:
• Pre conference courses (Sunday, 27 August)
• Invited and plenary sessions (Monday to Wednesday, 28-30 August)
• Mini-symposia (Thursday, 31 August)
• Early Career Biostatisticians’ Day (Thursday, 31 August)
Social events will include:
• Student gathering (Sunday, 27 August)
• Welcome reception (Monday, 28 August)
• Half-day excursions (Tuesday, 29 August)
• Social dinner (Wednesday, 30 August)
The Wednesday and Thursday program will be jointly organised by ISCB (International Society for Clinical Biostatistics) and the Italian region of IBS (International Biometric Society).
Updated information will be posted regularly on the conference website.
The deadline for abstract submission will be 10 March 2023.
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Local Organizing Committee (LOC)
Chair: Maria Grazia Valsecchi
Vice-chair: Laura Antolini
Treasurer: Paola Rebora
Davide Bernasconi
Valeria Edefonti
Aldo Solari
Scientific Programme Committee (SPC)
Chair: Stefania Galimberti (IT)
Claudia Angelini (IT)
Jonathan Bartlett (UK)
Stefano Calza (IT)
Clelia Di Serio (IT)
Malka Gorfine (IL)
Dario Gregori (IT)
Thomas Jaki (UK & DE)
Thomas Lumley (NZ)
Rajarshi Mukherjee (US)
Cécile Proust-Lima (FR)
Marie Reilly (SE)
Kaspar Rufibach (CH)
Thomas Scheike (DK)
Ewout Steyerberg (NL)
Francesco Stingo (IT)
Giota Touloumi (GR)
James Wason (UK)
Emily C. Zabor (US)
Mini-Symposia Committee (MSC)
Chair: Marco Bonetti
Federico Ambrogi
Emanuele Di Angelantonio
Stefania Galimberti
Mauro Gasparini
Maria Luisa Restaino
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Main conference topics
• Bayesian theory and computation
• Biomarker discovery, development and validation
• Causal inference and causal machine learning
• Competing risks and multistate models
• Covid19 spread, diagnosis and interventions
• High dimensional data
• Innovative clinical trial designs
• Innovative epidemiological designs
• Latent variable modelling
• Longitudinal and correlated data
• Machine learning and deep learning methods for health
• Methods for rare diseases
• Missing data
• Non parametric and semiparametric methods
• Precision medicine
• Prediction models
• Real world data
• Statistics in epidemiology
• Survival analysis