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Registration opens August 15th at www.idwsds.org.
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Tuesday, October 6
 

10:00 UTC

S306 - Modern Statistical Methods and Applications in Health Research
Tuesday October 6, 2026 10:00 - 11:00 UTC
This session highlights the breadth of biostatistics through four distinct but complementary talks by statistical researchers. It explores how modern statistical methodologies are advancing health research by addressing challenges in evidence generation, clinical decision-making, and causal inference. The presentations cover Bayesian learning frameworks for individualised treatment recommendations, large language model-assisted tools that improve the efficiency and reproducibility of systematic reviews and meta-analyses, innovative clinical trial designs and the practical challenges that influence their efficiency, and Mendelian randomisation approaches for investigating causal relationships and therapeutic targets in cardiovascular disease. Together, these talks aim to strengthen the reliability, transparency and translation of evidence, thereby supporting more informed clinical and public health decision-making in an increasingly connected global health research landscape.
Speakers
avatar for Pamela Massiel Chiroque Solano

Pamela Massiel Chiroque Solano

University of Regensburg
Pamela Solano is a statistician passionate about transforming complex data into trustworthy clinical decisions. As a researcher at the Faculty of Informatics and Data Science, University of Regensburg, Germany, she develops interpretable AI and Bayesian learning methods that empower... Read More →
avatar for Danyang Dai

Danyang Dai

The University of Sydney
Danyang Dai (Daidai) is a final year PhD student (thesis submitted) at the Queensland Digital Health Centre. She is an applied statistician and infectious disease epidemiology researcher with expertise in large scale health data analysis, disease surveillance, and advanced statistical... Read More →
avatar for Aritra Mukherjee

Aritra Mukherjee

Newcastle University
Aritra Mukherjee is a Research Associate in the Biostatistics Research Group at Newcastle University. Her research focuses on developing innovative statistical methods for clinical trials, with expertise in adaptive trial designs such as multi-arm multi-stage (MAMS) trials, sample... Read More →
avatar for Daianna Gonzalez Padilla

Daianna Gonzalez Padilla

University of Cambridge
Researcher in Genetic Epidemiology at the MRC Biostatistics Unit, University of Cambridge, specializing in Mendelian randomization, a causal inference framework that uses genetic variants to assess the effects of putative risk factors on disease from observational data. My research... Read More →
Chairs/Hosts Organizers
Tuesday October 6, 2026 10:00 - 11:00 UTC
Zoom Room #3
 
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