All Session Tracks

• Track 01 – Advancements in Survival Analysis Techniques
  This track focuses on the latest methodologies and innovations in survival analysis, emphasizing new statistical techniques and their applications. Researchers are encouraged to present novel approaches that enhance the understanding of time-to-event data. Aligned SDGs: SDG 3 – Good Health and Well-being  |  SDG 4 – Quality Education
• Track 02 – Hazard Models and Their Applications
  This session will explore various hazard models used in survival analysis, including proportional hazards and accelerated failure time models. Participants will discuss practical applications in fields such as biostatistics and epidemiology. Aligned SDGs: SDG 3 – Good Health and Well-being  |  SDG 9 – Industry, Innovation and Infrastructure
• Track 03 – Reliability Theory in Time-to-Event Data
  This track addresses the intersection of reliability theory and survival analysis, focusing on the modeling of failure times and reliability functions. Contributions should highlight theoretical advancements and real-world applications. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 3 – Good Health and Well-being
• Track 04 – Statistical Methods for Clinical Data Analysis
  This session invites discussions on statistical methodologies specifically tailored for analyzing clinical trial data. Emphasis will be placed on time-to-event outcomes and the implications for patient care. Aligned SDGs: SDG 3 – Good Health and Well-being  |  SDG 4 – Quality Education
• Track 05 – Predictive Analytics in Survival Studies
  This track will delve into the use of predictive analytics in survival analysis, showcasing techniques that enhance forecasting and decision-making. Researchers are encouraged to present case studies demonstrating the impact of predictive models. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 3 – Good Health and Well-being
• Track 06 – Machine Learning Approaches to Time-to-Event Modeling
  This session focuses on the integration of machine learning techniques with traditional survival analysis methods. Participants will explore how these approaches can improve model accuracy and interpretability. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 4 – Quality Education
• Track 07 – Quantitative Methods in Epidemiological Research
  This track highlights the application of quantitative methods in epidemiological studies, particularly in analyzing time-to-event data. Contributions should focus on innovative statistical techniques that address public health challenges. Aligned SDGs: SDG 3 – Good Health and Well-being  |  SDG 4 – Quality Education
• Track 08 – Simulation Techniques in Survival Analysis
  This session will cover the role of simulation in the development and validation of survival analysis models. Researchers are invited to share insights on simulation methodologies and their practical applications. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 4 – Quality Education
• Track 09 – Risk Analysis and Management in Time-to-Event Studies
  This track will explore risk analysis frameworks within the context of time-to-event data, focusing on identifying and managing risks in various domains. Contributions should highlight both theoretical and applied perspectives. Aligned SDGs: SDG 3 – Good Health and Well-being  |  SDG 9 – Industry, Innovation and Infrastructure
• Track 10 – Data Science Innovations in Survival Analysis
  This session will examine the role of data science in advancing survival analysis methodologies, including data mining and big data techniques. Participants are encouraged to present interdisciplinary approaches that leverage data science tools. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 4 – Quality Education
• Track 11 – Artificial Intelligence in Biostatistics and Survival Analysis
  This track will explore the application of artificial intelligence in biostatistics, particularly in modeling and analyzing survival data. Researchers are invited to discuss the potential of AI to transform traditional statistical practices. Aligned SDGs: SDG 3 – Good Health and Well-being  |  SDG 9 – Industry, Innovation and Infrastructure

Alignment with the Sustainable Development Goals
Alongside its academic focus, the conference promotes responsible research, ethical practice and knowledge-driven development. Its session tracks collectively contribute to the following United Nations Sustainable Development Goals.

• SDG 3
  Good Health and Well-being
• SDG 4
  Quality Education
• SDG 9
  Industry, Innovation and Infrastructure