International Conference on Biostatistics and Epidemiological Modeling

ICBEM

21st Sep – 22nd Sep 2026 Munich, Germany

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Registration Summary

Conference ICBEM

Date 21st Sep – 22nd Sep 2026

Location Munich, Germany

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

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Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Advancements in Biostatistical Methods +

This track focuses on the latest developments in biostatistical methodologies applicable to health research. Emphasis will be placed on innovative statistical techniques that enhance data analysis in clinical and epidemiological studies.

SDG 3 SDG 4

02 Epidemiological Modeling Approaches +

This session will explore various modeling approaches used in epidemiology to understand disease dynamics. Participants will discuss the implications of these models for public health decision-making and policy formulation.

SDG 3 SDG 16

03 Predictive Analytics in Healthcare +

This track will delve into the application of predictive analytics in healthcare settings, focusing on techniques that improve patient outcomes. Case studies demonstrating successful implementations of predictive models will be highlighted.

SDG 3 SDG 9

04 Statistical Simulation Techniques +

This session will cover the role of simulation in statistical analysis, particularly in biostatistics and epidemiology. Participants will examine various simulation methods and their applications in real-world scenarios.

SDG 3 SDG 9

05 Regression Techniques in Biostatistics +

This track will focus on advanced regression techniques used in biostatistical research. Discussions will include the application of these methods in analyzing clinical data and longitudinal studies.

SDG 3 SDG 9

06 Bayesian Methods in Epidemiology +

This session will explore the application of Bayesian methods in epidemiological research, emphasizing their advantages in handling uncertainty. Participants will discuss case studies that illustrate the effectiveness of Bayesian approaches.

SDG 3 SDG 16

07 Survival Analysis Techniques +

This track will address various techniques used in survival analysis, with a focus on their application in clinical trials and public health studies. The session aims to enhance understanding of time-to-event data analysis.

SDG 3 SDG 4

08 Longitudinal Data Analysis +

This session will explore methodologies for analyzing longitudinal data, particularly in the context of public health research. Emphasis will be placed on the challenges and solutions associated with repeated measures data.

SDG 3 SDG 4

09 Risk Analysis and Management +

This track will focus on statistical methods for risk analysis in health-related fields. Participants will discuss frameworks for assessing and managing risks associated with various health interventions.

SDG 3 SDG 16

10 Experimental Design in Health Research +

This session will cover the principles of experimental design and their application in biostatistics and epidemiology. Discussions will highlight best practices for designing studies that yield valid and reliable results.

SDG 3 SDG 4

11 Statistical Inference and Its Applications +

This track will explore the principles of statistical inference and their practical applications in biostatistics. Participants will engage in discussions on how inference techniques can inform public health policies and clinical practices.

SDG 3 SDG 16