Next-Gen Lifetime Data Analysis: Emerging Innovations and Applications

This book showcases innovative statistical and biostatistical approaches for complex lifetime data analysis in the era of artificial intelligence. It covers a wide range of topics in the rapidly evolving fields of lifetime data analysis in the AI era, including:

Statistical procedures and data analysis in lifetime data analysis

Bayesian survival analysis

Analysis of informatively censoring lifetime data

Current status lifetime data analysis

Interval-censored lifetime data analysis

Clinical trials

Competing risk analysis

Survival analysis and joint modeling

Residual analysis of lifetime data

Cure models

This book provides essential insights into cutting-edge methodologies and practical applications, making it an invaluable resource for professionals, researchers, and graduate students in biostatistics, bioinformatics, and data science. The contributors are distinguished researchers and applied scientists that discusses statistical methodologies, innovative approaches in lifetime data analysis, and their applications in biostatistics, bioinformatics, public health, and neuroscience.

As a timely and authoritative resource, it serves as a reference for professionals, researchers, and graduate students, helping to identify new directions in lifetime data analysis-related research. The latest advancements presented in this volume are invaluable for both practitioners and academics seeking to navigate the evolving landscape of statistical science and data analytics.