Mihail Popescu, PhD

Mihail Popescu, PhD

Biomedical Informatics, Biostatistics and Medical Epidemiology (BBME)

Professor

573-882-1266

Profile

Dr. Popescu's research areas include biomedical intelligent systems and eldercare. His current research focuses on developing decision support systems for eldercare and chronic disease management. Chronic diseases such as diabetes, heart failure or depression decrease the quality of life and increase the risk of re-hospitalization. Dr. Popescu is currently investigating new technologies for eldercare such as new sensors, new monitoring technologies and new machine learning algorithms used to avoid this decrease. His research in early recognition of chronic conditions is intended to improve the quality of life and reduce the cost of health care. Dr. Popescu is developing novel summarization and visualization methodologies to address the health care big data problem associated with the patient activity monitoring process.

 
 

Academic Information

Professor
P. 573-882-1266

Research Interests

  • Pattern recognition
  • Image processing
  • Computational intelligence
  • Agent based modeling
  • Eldercare technologies
  • Sensoromics
  • Mass behavior modeling
  • Landmine detection

Areas of Expertise

  • Machine learning
  • Image processing
  • Intelligent Systems
  • Eldercare technologies
  • Sensoromics

Publications

  • M. Rantz, T. Banerjee, E. Cattoor, S. Scott, M. Skubic, M. Popescu, "Automated Fall Detection With Quality Improvement "Rewind" to Reduce Falls in Hospital Rooms", J of Gerontological Nursing, Vol. 40, No. 1, 2014, pp. 13-17.
  • Y. Li, D. Ho, M. Popescu, "Efficient source separation algorithms for acoustic fall detection using a Microsoft Kinect", IEEE Trans. on Biomedical Engineering, vol. 61, no. 3, March 2014.
  • M. Rantz, M. Skubic, S. Miller, C. Galambos, G. Alexander, J. Keller, M. Popescu, "Sensor Technology to Support Aging in Place", JAMDA, 14(6), 2013, pp. 386-391.
  • M. Popescu, J.C. Bezdek, T. Havens, J.M. Keller, "A Cluster Validity Framework based on Induced Partition Dissimilarity", IEEE Trans. on System, Man, Cybernetics Part B, Vol. 43, No.1, 2013, pp.308-320.
  • M. Popescu, A. Mahnot, "Early Illness Recognition in Older Adults Using In-Home Monitoring Sensors and Multiple Instance Learning", Methods of Informatics in Medicine, 2012 Aug 7;51(4):359-67.
  • Y. Li, D. Ho, M. Popescu, "Microphone Array System for Automatic Fall Detection", IEEE Transactions on Biomedical Engineering, vol. 59, pp. 1291-1301, May 2012.
  • M. Khalilia, S. Chakraborty, M. Popescu, "Predicting Disease Risks from Highly Unbalanced Data using Random Forest", BMC Medical Informatics and Decision Making, 2011, 11:51.
  • M. Popescu, G. Arthur, F. Rahmatpanah, O. Sjahputera, J. Keller, H. Shi, C.W. Caldwell, "A Minimum Classification Error Framework Suitable for Multi-criteria Gene Selection: Discovery of Differentially Methylated Genes in Small B-Cell Lymphomas", International Journal of Computational Intelligence in Bioinformatics and Systems Biology, vol.1, no.3, 2010.
  • M. Popescu, E. Florea, Linking Clinical Events in Elderly to In-home Monitoring Sensor Data: A Brief Review and a Pilot Study on Predicting Pulse Pressure", Journal of Computing Science and Engineering, vol. 2, no. 1, March 2008, pp. 180-199.
  • M. Popescu, J.M. Keller, J.A. Mitchell, "Fuzzy Measures on the Gene Ontology for Gene Product Similarity", IEEE Trans. Computational Biology and Bioinformatics, vol. 3, no. 3, pp. 1-11, July-September 2006.
  • M. Popescu, P.D. Gader, J.M. Keller, "Fuzzy Spatial Pattern Processing Using Linguistic Hidden Markov Models", IEEE Transactions on Fuzzy Systems, vol. 14, no. 1, pp. 81-92, February 2006.