Partially Observable Markov Chain Models for Evaluating Lung Cancer Screening Policies. - Nicholas Prayogo; Davood Pirayesh Neghab; Syed Mahbub Rafayal; Mucahit Cevik (CASCON, 2022)

A multi-objective constrained POMDP model for breast cancer screening. - Can Kavaklioglu; Mucahit Cevik; Robert Helmeczi; Davood Pirayesh Neghab (CoRR, 2022)

An integrated data-driven method using deep learning for a newsvendor problem with unobservable features. - Davood Pirayesh Neghab; Siamak Khayyati; Fikri Karaesmen (Eur. J. Oper. Res., 2022)

Identifying the Factors Influencing IPO Underpricing using Explainable Machine Learning Techniques. - Davood Pirayesh Neghab; Mucahit Cevik; Ayse Basar (Canadian AI, 2023)

Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning. - Davood Pirayesh Neghab; Mucahit Cevik; M. I. M. Wahab (CoRR, 2023)

A multi-objective constrained partially observable Markov decision process model for breast cancer screening. - Robert K. Helmeczi; Can Kavaklioglu; Mucahit Cevik; Davood Pirayesh Neghab (Oper. Res., 2023)