Abstract Background and Aims Chronic inflammatory demyelinating polyneuropathy (CIDP)
is a rare immune‐mediated disease of the peripheral nerves, with significant unmet …

Abstract Machine Learning Models are known to understand the intricacies of the data well,
but native ML models cannot be used in time-to-event analysis due to censoring. In this …

Background and Objectives Bayesian analysis of randomized controlled trials (RCTs) can
extend the value of trial data beyond interpretations based on conventional p value–based …

Survival prediction, central to the analysis of clinical trials, has the potential to be
transformed by the availability of RNA-seq data as it reveals the underlying molecular and …

Oncology has been one of the most active therapeutic areas in medicinal products
development. Despite this fact, few drugs have been approved for use in pediatric cancer …

Dengue Hemorrhagic Fever (DHF) is currently attacking residential areas unprepared to
prevent the spread of the Aedes Aegypti mosquito. This has resulted in many residents …

The complex multimodality in clinical and liquid biopsy data generated by multiparametric
diagnostic and tumor profiling technologies presents an exciting opportunity for developing …

Bayesian inference for survival regression modeling offers numerous advantages,
especially for decision-making and external data borrowing, but demands the specification …

PARAMETRIC MODELLING USING BAYESIAN APPROACH 1. Introduction Survival
analysis is one of the most important fields of Statistics Page 1 Unilag Journal of …

Conclusions• When relevant historical trial data are integrated into a survival model
appropriately, this information can improve the reliability of short-and long-term …