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Ali Dag, PhD

Associate Professor

Accounting and Business Intelligence and Analytics

Ali Dag

Contact

Heider College of Business
Accounting and Business Intelligence & Analytics - Business
Business Analytics (Graduate Certificate)
Analytics (Master of Science)
Business Intelligence and Analytics (Master of Science)
Graduate School
HARP - Harper Center for Student Life & Learn

Ali Dag, PhD

Associate Professor

Accounting and Business Intelligence and Analytics

BIA 479B : Machine Learning
BIA 781N : Machine Learning

Teaching Interests

  • Machine Learning

Research Focus

Business & Data Analytics, Heatlhcare Operations, Machine Learning in Business Applications, Operations Research

Department

Accounting and Business Intelligence & Analytics

Position

Associate Professor

Articles

  • Elsevier
    A hybrid data mining approach for identifying the temporal effects of variables associated with breast cancer survival 2019
  • Emerald
    A comparative data analytic approach to construct a risk trade-off for cardiac patients’ re-admissions
    119&1, p. 189-209 2019
  • Elsevier
    Predicting graft survival among kidney transplant recipients: A Bayesian decision support model
    106, p. 97-109 2018
  • Springer
    An AHP-IFT Integrated Model for Performance Evaluation of E-Commerce Web Sites, p. 1-11 2018
  • The Impact of Cultural Perception on the Individual Health Care Consumer: A Comparison of Germany and United States
    3, p. 252-258 2018
  • Factors Associated with Readmission of Cardiac Patients
    6-4, p. 2372–5079 2018
  • Elsevier
    Predicting heart transplantation outcomes through data analytics
    94, p. 42-52 2017
  • Springer
    Measuring the efficiency of hospitals: a fully-ranking DEA–FAHP approach, p. 1-18 2017
  • Elsevier
    A probabilistic data-driven framework for scoring the preoperative recipient-donor heart transplant survival
    86, p. 1-12 2016
  • Springer International Publishing
    A machine learning-based approach to predict the velocity profiles in small streams
    30&1, p. 43-61 2016
  • Elsevier
    A Bayesian network-based data analytical approach to predict velocity distribution in small streams
    18 & 3, p. 466-480 2015