Faculty profile
Mucahit Cevik
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Research
Latest papers
Interpretable machine learning for personalized breast cancer screening recommendations
Health Care Management Science · 2026 · senior author
Improving hard-to-place kidney allocation: A machine learning approach to center ranking
Health Care Management Science · 2026
Predicting offer burden to optimize batch sizes in simultaneously expiring kidney offers
Frontiers in Artificial Intelligence · 2025 · senior author
Latest funding
- $74,973
Stochastic Optimization Models for Hybrid Workforce Scheduling
SSHRC · 2026 · Principal investigator
- $182,000
Novel optimization methods for cancer screening and treatment
NSERC · 2019 · Principal investigator
- $12,500
Novel optimization methods for cancer screening and treatment
NSERC · 2019 · Principal investigator
9 publications.
Interpretable machine learning for personalized breast cancer screening recommendations
Berry S, Görgülü B, Tunc S, Cevik M
Improving hard-to-place kidney allocation: A machine learning approach to center ranking
Berry S, Görgülü B, Tunç S, Cevik M, Ellis MJ
Predicting offer burden to optimize batch sizes in simultaneously expiring kidney offers
Berry S, Görgülü B, Tunç S, Cevik M
Sequence Labeling for Disambiguating Medical Abbreviations.
Cevik M, Mohammad Jafari S, Myers M, Yildirim S
Active Learning for Multi-way Sensitivity Analysis with Application to Disease Screening Modeling.
Cevik M, Angco S, Heydarigharaei E, Jahanshahi H, Prayogo N
Auto Response Generation in Online Medical Chat Services.
Jahanshahi H, Kazmi S, Cevik M
Word-level text highlighting of medical texts for telehealth services.
Ozyegen O, Kabe D, Cevik M
Evaluation of interpretability methods for multivariate time series forecasting.
Ozyegen O, Ilic I, Cevik M
The University of Wisconsin Breast Cancer Epidemiology Simulation Model: An Update.
Alagoz O, Ergun MA, Cevik M, Sprague BL, Fryback DG, Gangnon RE, Hampton JM, Stout NK, Trentham-Dietz A
Stochastic Optimization Models for Hybrid Workforce Scheduling
Principal investigators: Cevik, Mucahit
Novel optimization methods for cancer screening and treatment
Principal investigators: Cevik, Mucahit
Keywords: markov decision processes; dynamic programming; integer programming; stochastic programming; discrete event simulation; cancer screening and treatment; medical decision making; health care delivery
Novel optimization methods for cancer screening and treatment
Principal investigators: Cevik, Mucahit
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
Frequent collaborators
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