Hanen Borchani

Short Bio:

Hanen Borchani received the master degree in Computer Science Applied to Management in June 2006 from the Higher Institute of Management of Tunis (ISG Tunis), and the Ph.D. degree in Artificial Intelligence in January 2013 from the Universidad Politécnica de Madrid (UPM). She is currently a post-doctoral researcher at the UPM and the Cajal Blue Brain Project. Her research interests include data mining, Bayesian networks, data streams, concept drift, semi-supervised learning, multi-dimensional classification, and applications to medicine and neuroscience.

Journal publications:

  • Borchani, H., Bielza, C., Martínez-Martín, P. & Larrañaga, P. (2013). Predicting EQ-5D from the Parkinson's disease questionnaire using multi-dimensional Bayesian network classifiers. Biomedical Engineering: Applications, Basis and Communications, Accepted for publication.
  • Borchani, H., Bielza, C., Toro, C. & Larrañaga, P. (2013). Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers. Artificial Intelligence in Medicine57(3), 219-229.
  • Borchani, H., Bielza, C., Martínez-Martín, P. & Larrañaga, P. (2012). Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39). Journal of Biomedical Informatics45, 1175-1184.
    • Borchani, H., Larrañaga, P. & Bielza, C. (2010). Classifying evolving data streams with partially labeled data. Intelligent Data Analysis, 15(5), 655-670.
    • Borchani, H., N. Ben Amor & F. Khalfallah. (2008). Learning and Evaluating Bayesian Network Equivalence Classes from Incomplete Data. International Journal of Pattern Recognition and Artificial Intelligence, 22(2), 253-278.