Ali Dag
Ali Dag
Associate Professor of Analytics, Heider College of Business, Creighton University
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Cited by
Cited by
Predicting graft survival among kidney transplant recipients: A Bayesian decision support model
K Topuz, FD Zengul, A Dag, A Almehmi
Decision Support Systems 106, 97-109, 2018
Predicting heart transplantation outcomes through data analytics
A Dag, A Yucel, S Bulur, FM Megahed
Decision Support Systems 94, 42-52, 2017
Measuring the efficiency of hospitals: a fully-ranking DEA–FAHP approach
BD Rouyendegh, J Ekong, A Dag
Annals of Operations Research, 1-18, 2017
A probabilistic data-driven framework for scoring the preoperative recipient-donor heart transplant survival
A Dag, K Topuz, S Bulur, MF Megahed
Decision Support Systems 86, 1-12, 2016
A hybrid data mining approach for identifying the temporal effects of variables associated with breast cancer survival
S Simsek, U Kursuncu, E Kibis, M AnisAbdellatif, A Dag
Expert Systems with Applications, 112863, 2020
An AHP-IFT Integrated Model for Performance Evaluation of E-Commerce Web Sites
BD Rouyendegh, K Topuz, A Dag
Information Systems Frontiers, 1-11, 2018
A comparative data analytic approach to construct a risk trade-off for cardiac patients’ re-admissions
M Nasir, C South-Winter, S Ragothaman, A Dag
Industrial Management & Data Systems 119 (1), 189-209, 2019
A Bayesian Belief Network-based probabilistic mechanism to determine patient no-show risk categories
S Simsek, A Dag, T Tiahrt, A Oztekin
Omega 100, 102296, 2021
Data analytics approaches for breast cancer survivability: comparison of data mining methods
E Kibis, E Buyuktahtakin, A Dag
Proceedings of the 2017 Industrial and Systems Engineering Conference, 2017
A machine learning-based approach to predict the velocity profiles in small streams
O Genš, A Dağ
Water resources management 30 (1), 43-61, 2016
Stratifying No-show Patients into Multiple Risk Groups via a Holistic Data Analytics-based Framework
S Simsek, T Tiahrt, A Dag
Decision Support Systems, 2020
Developing a Decision Support System to Detect Material Weaknesses in Internal Control
M Nasir, S Simsek, E Cornelsen, S Ragothaman, A Dag
Decision Support Systems, 2021
Impact of commitment, information sharing, and information usage on supplier performance: a Bayesian belief network approach
A Sener, M Barut, A Dag, MB Yildirim
Annals of Operations Research, 1-34, 2019
A Bayesian network-based data analytical approach to predict velocity distribution in small streams
O Genc, A Dag
Journal of Hydroinformatics 18 (3), 466-480, 2016
A service analytic approach to studying patient no-shows
M Nasir, N Summerfield, A Dag, A Oztekin
Service Business, 1-27, 2020
Determining Optimal Skillsets for Business Managers Based on Local and Global Job Markets: A Text Analytics Approach
M Nasir, A Dag, WA Young, D Delen
Decision Sciences Journal of Innovative Education 18 (3), 374-408, 2020
A Bayesian approach to detect the firms with material weakness in internal control
S Simsek, E Bayraktar, S Ragothaman, A Dag
2018 Institute of Industrial and Systems Engineers Annual Conference andá…, 2019
Factors associated with readmission of cardiac patients
CA South-Winter, A Dag, S Ragothaman
International Journal of Health Sciences 6 (4), 2372-5079, 2018
Preface : Data Mining & Decision Analytics
VCP Chen, SB Kim, A Dag
Annals of Operations Research 303 (1-3), 2021
Predicting hotel reviews from sentiment: a multinomial classification framework
A Yucel, M Caglar, HA Dolatsara, B George, A Dag
Journal of Modelling in Management 17 (2), 697-714, 2021
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