Classification, Survival analysis, Clinical trials, Bayesian survival modeling,
Feature selections, High-dimensional gene expression data analysis
Kumari, P., Vishwakarma, G. K. & Bhattacharjee, A. (2026). Classification of lung cancer patients in multi-stages based on gene expressions, Communications in Statistics-Simulation and Computation. link
Kumari, P.*, Vishwakarma, G. K., Bhattacharjee, A. & Ong S.H. (2025). Bayesian classifier based on cancer prognostic markers using accelerated failure time model with frailty effect, Quality & Quantity. link
Kumari, P., Bhattacharjee, A., Vishwakarma, G. K., & Tank F. (2025). afthd: Bayesian accelerated failure time model for high-dimensional time-to-event data, Japanese Journal of Statistics and Data Science link.
Bhattacharjee, A., Basak, S., & Kumari, P. (2023). A two-step feature selection procedure for relevant markers of Squamous Cell Lung Carcinoma using different survival models. Healthcare Analytics, 3, 100168. link
Vishwakarma, G. K., Kumari, P.*, & Bhattacharjee, A. (2022). Thresholding of prominent biomarkers of breast cancer on overall survival using classification and regression tree. Cancer Biomarkers, 34(2), 319-328. link
Bhattacharjee, A., Dey, J., & Kumari, P. (2022). A combined iterative sure independence screening and Cox proportional hazard model for extracting and analyzing prognostic biomarkers of adenocarcinoma lung cancer. Healthcare Analytics, 2, 100108. link
Bhattacharjee, A., Vishwakarma, G.K., & Kumari, P. (2021). afthd: Accelerated Failure Time for High Dimensional Data with MCMC. R package, version 0.1.0. CRAN. \url