Arpad Kelemen, PhD

Associate Professor, OSAH
Address: 455B
Phone Number: 410-706-1417
Fax Number: 410-706-3289
kelemen@umaryland.edu

Education

  • PhD, Computer Science, University of Memphis, 2002
  • MS, Computer Science, University of Szeged, Hungary, 1995
  • BS, Computer Science, University of Szeged, Hungary, 1993

Research

  • MADE CLEAR - NSF Climate Change Grant "Creating an IPE Climate Change Elective". Role: Co-PI. 2016-2017. Funded for $5,000.
  • HSCRC "Expanding Clinical Informatics Educational Grant". Role: Co-I. PI: Linda Hickman. 2016-2017.
  • HRSA "Nursing Informatics Program Focused on Diversity and the Underserved". Role: PI. 2009-2011. Funded for $467,741.
  • HSCRC "The Doctor of Nursing Practice: An Initiative to Increase Maryland's Nursing Faculty" Role: Co-I. PI: Patricia Morton. 2009-2011. Funded for $1,020,000.
  • NSF "Advanced Bayesian Approaches for Heterogeneous Temporal Genomic MetaData" Role: Co-PI. 2006-2009. Funded for $144,999.
  • NSF "CISE Computing Research Infrastructure" Role: Co-I. PI: Russ Miller. 2005-2008. Funded for $800,000.
  • National Institute of General Medical Sciences (NIH) subcontract: Buffalo Center for Biomedical Computing grant from Title: "Bayesian Meta-Analysis of Heterogeneous Genomic Data through Hybrid Systems", Role: Co-PI. 2004-2005. Funded for $30,000.
  • NYSTAR faculty development grant. Role: Co-I. PI: Alan Hutson 2004. Funded for $19,000.
  • NYSTAR faculty development grant. Role: Co-I. PI: Alan Hutson 2003. Funded for $18,750.
  • University of Maryland, Medical Center Quality and Safety Grant. "Development of a Web-Based Game for Patients on Warfarin or Coumadin", Role: PI 2011-2012. Funded for $5,000.
  • University of Maryland, School of Nursing DRIF Fund. "Improving Patient Outcomes in Low Health Literacy Populations with Mobile Games" Role: PI. 2012-2013. Funded for $10,000.
  • University of Maryland, School of Nursing Research Facilitation Grant "Mobile game application development for improving patient mobility in oncology" Role: PI. 2016-2017. Funded for $1,000.
  • Niagara University’s Research Grant, "Pattern Differentiations and Formulations for Heterogeneous Genomic Data through Hybrid Approaches", Role: PI. 2006. Funded for $5,200.
  • Niagara University’s Mini Grant Role: PI. 2006. Funded for $1720.
  • Niagara University’s Research Support Grant. 2006. Role: PI. Funded for $2800.
  • University of Mississippi’s Research Support Grant "Bioinformatics Research with Intelligent Techniques". Role: PI. 2002-2003. Funded for: $30,000.

Publications

  • Liang, Y., Kelemen, A. (2017). Dynamic Modeling and Network Approaches for Omics Time Course Data: Overview of Computational Approaches and Applications, Brief Bioinform 2017 bbx036. doi: 10.1093/bib/bbx036
  • Liang, Y., Kelemen, A., (2017) Shared Polymorphisms and Modifiable Behavior Factors for Myocardial Infarction and High Cholesterol in a Retrospective Population Study, Journal of Medicine, 96(37): e7683. doi: 10.1097/MD.0000000000007683.
  • Liang, Y., Kelemen, A., (2017). Computational Dynamic Approaches for Temporal Omics Data with Applications to System Medicine. BioData Mining 10:20 DOI: 10.1186/s13040-017-0140-x
  • Estes, S. L., Kelemen, A., Liang, Y., Constantine, D. R. (2016). “Electronic Health Record Vendors in Reducing Hospital Readmission Rates: Promoting Interoperability” Informatics Nursing 1(2): 6-14.
  • Tagaytayan, R., Kelemen, A., Sik-Lanyi, C. (2016). “Augmented Reality in Neurosurgery” Archives of Medical Science 1-7. https://doi.org/10.5114/aoms.2016.58690
  • Liang, Y., Kelemen, A. (2016). “Bayesian State Space Models for Dynamic Genetic Network Construction Across Multiple Tissues” Statistical Applications in Genetics and Molecular Biology 15(4):273-90. doi: 10.1515/sagmb-2014-0055.
  • Liang, Y., Kelemen, A. (2016). “Big Data Science and its Applications in Healthcare and Medical Research: Challenges and Opportunities”, Austin Biom and Biostat  3(1): 1030
  • Yates, M., Kelemen, A., Sik-Lanyi, C. (2016). “Virtual reality gaming in the rehabilitation of the upper extremities post-stroke” Brain Injury 30(7):855-63. doi: 10.3109/02699052.2016.1144146
  • Moerbe, M., Kelemen, A. (2014). “Turning EHR Data into Meaningful Information Using SQL and Nursing Informatics” Comput Inform Nurs. 32(8): 366–377 doi: 10.1097/CIN.0000000000000079
  • Castillo, R. S., Kelemen, A. (2013). “Considerations for a successful clinical decision support system” Computers, Informatics, Nursing 31(7): 319-26 doi: 10.1097/NXN.0b013e3182997a9c
  • Faddoul, B., Kelemen, A, Connerney, I., Grover, B., Hoffman, J. (2012). “Patients’ Perceptions of a Game about Vitamin K and Warfarin: A Pilot Study” Games for Health Journal 1, 362-368.
  • Kelemen, A., Liang, Y. (2012). “Multi-Center Correction Functions for Magnetization Transfer Ratios of MRI Scans” Journal of Health & Medical Informatics S3. doi: 10.4172/2157-7420.S3-002
  • Liang, Y., Kelemen, A. (2011). “Sequential support vector regression with embedded entropy for SNP selection and disease classification”, Journal of Statistical Analysis and Data Mining doi: 10.1002/sam.10110.
  • Katsuya, K., Kelemen, A. (2011). “A Systematic Review of Intelligent Patient Care Assistive Technology: Toward a Revolution of Nursing Practice” Computers Informatics Nursing 29(8), 441-442 DOI: 10.1097/NCN.0b013e3182305d5a
  • Kelemen, A., Vasilakos, AV., Liang, Y. (2009). “Computational Intelligence in Bioinformatics: SNP/haplotype data in Genetic Association Study for Common Diseases” IEEE Transactions on Information Technology in Biomedicine 13(5):841-7.
  • Liang, Y., Kelemen, A. (2009) “Bayesian Finite Markov Mixture Model for Temporal Multi-Tissue Polygenic Patterns” Biometrical Journal 51(1):56-69.
  • Kelemen, A., Vasilakos, A., Liang, Y. (2009). “Computational Intelligence for Genetic Association Study in Complex Diseases: Review of Theory and Applications”, International Journal of Computational Intelligence in Bioinformatics and Systems Biology, 1(1): 15-31.
  • Liang, Y., Kelemen, A. (2009). “Time Lagged Recurrent Neural Network for Temporal Gene Expression Classification”, International Journal of Computational Intelligence in Bioinformatics and Systems Biology 1(1):86-99.
  • Tayo, B., Liang, Y., Kelemen, A., Miller, A., Trevisan, M., Cooper, R. (2009). “Use of supplementary phenotype to identify additional rheumatoid arthritis loci in a linkage analysis of 342 UK affected sibling pair families”, BMC Medical Genetics 10(1):142. doi:10.1186/1471-2350-10-142.
  • Dalaker, T. O.,  Larsen, J. P, Bergsland, N., Beyer, M., Alves, G., Dwyer, M.G., Tysnes, O. B., Benedict, R. H. B., Kelemen, A., Zivadinov, R. (2009) “Brain atrophy and white matter hyperintensities in early Parkinson’s Disease”, Movement Disorders, DOI 10.1002/mds.22754.
  • Kelemen, A., Liang, Y., Vasilakos, A.(2008) “Review of Computational Intelligence for Gene-Gene and Gene-Environment Interactions in Disease Mapping”, in “Computational Intelligence in Medical Informatics” (A. Kelemen, A. Abraham, Y. Liang, Eds.) in the Series in “Studies in Computational Intelligence”, Springer-Verlag, Heidelberg, Germany, pp. 1-16.
  • Liang, Y., Kelemen, A. (2008) “Time Course Gene Expression Classification with Time Lagged Recurrent Neural Network”, in “Computational Intelligence in Bioinformatics” (A. Kelemen, A. Abraham, Y. Chen, Eds.) in the Series in “Studies in Computational Intelligence”, Springer-Verlag, Heidelberg, Germany, pp. 149-164.
  • Liang, Y., Kelemen, A., (2008) “Bayesian Models and Meta Analysis for Multiple Tissue Gene Expression Data Following Corticosteroid Administration” BMC Bioinformatics, 9:354.
  • Dalaker, T. O., Larsen, J. P., Bergsland, N., Beyer, M., Alves, G., Dwyer, M. G., Tysnes, O. B., Benedict, R. H. B., Kelemen, A., Zivadinov, R. (2008) “Extent of brain atrophy and white matter hyperintensities in early Parkinson Disease.  A large case-control study”, Neurology, 70 (Suppl 1): P08.023, A437.
  • Dwyer, M. G., Stosic, M., Hussein, S., Kelemen, A., Wack, D., Zivadinov, R. (2008) “A voxel-wise random field theory-based magnetization transfer approach for detecting focal demyelination and remyelination in multiple sclerosis”, Neurology, 70 (Suppl 1): P08.150, A466.
  • Kelemen, A., Dwyer, M. G., Horakova, D., Vaneckova, M., Havrdova, E., Zivadinov, R. (2008) “Measurement of gray matter volume is less susceptible to pseudoatrophy effect than that of white matter or whole brain volume in patients with multiple sclerosis. Results from Avonex-Steroids-Azathioprine combination study”. Multiple Sclerosis, 14 (Suppl 1): 280:S11.
  • Kelemen, A., Dwyer, M., Hussein, S., Stosic, M., Liang, Y., Zivadinov, R. (2008) Can magnetization transfer data from different magnetic resonance imaging scanner/sequence/pulse types be standardized? An application of correction factor function method. Multiple Sclerosis, 14 (Suppl 1): P279:S111.
  • Passanese, J., Kelemen, A., Weinstock-Guttman, B., Teter, B., Mihai, C., Hojnacki, D., Munschauer, F., E., Abdelrahman, N., Stosic, M., Zivadinov, R. (2008) “Protective clinical, demographic and conventional and non-conventional MRI predictors of benign multiple sclerosis. A large cohort study”, Multiple Sclerosis, 14 (Suppl 1): P629:S214.
  • Passanese, J., Kelemen, A., Weinstock-Guttman, B., Teter, B., Mihai, C., Hojnacki, D., Munschauer, F., E., Abdelrahman, N., Stosic, M., Zivadinov, R. (2008) “Conventional and non-conventional quantitative magnetic resonance imaging outcomes differ when comparing multiple definitions of benign multiple sclerosis”, Multiple Sclerosis, 14 (Suppl 1): P630:S214.
  • Liang, Y., Kelemen, A. (2008) “Statistical Advances and Challenges for Analyzing Correlated High Dimensional SNP Data in Genomic Study for Complex Diseases”, Statistics Surveys Vol. 2, 43-60.
  • Liang, Y., Kelemen, A. (2007) “Bayesian State Space Models for Inferring and Predicting Temporal Gene Expression Profiles”. Biometrical Journal 49(6) 801-814.
  • Liang, Y., Kelemen, A., Tayo, B. O. (2007) “Model Based or Algorithms Based? Gene Expression Based Statistical Methods to Find Evidence of Diabetes”. Journal of Statistical Methods in Medical Research 16(2): 139-153.
  • Liang, Y., Kelemen, A. (2006) “Associating phenotypes with molecular events: a review of statistical advances and challenges underpinning microarray analyses”. Journal of Functional and Integrative Genomics Vol. 6, pp. 1-13.
  • Kelemen, A., Liang, Y. (2006) “Pattern Differentiations and Formulations for Heterogeneous Genomic Data through Hybrid Approaches”, (H. Hsu, ed.), in “Advanced Data Mining Technologies in Bioinformatics”, Idea Group Inc. Press, pp. 136-154.
  • Kelemen, A., Franklin, S., Liang, Y. (2005) “Constraint Satisfaction in Conscious Software Agents - A Practical Application”, Journal of Applied Artificial Intelligence 19:491-514.
  • Kelemen, A., Liang, Y., Franklin, S. (2005) “Learning High Quality Decisions with Neural Networks in “Conscious” Software Agents”, Journal of World Scientific and Engineering Academy and Society 9(4), pp.1482-1492.
  • Liang, Y., Tayo, B., Cai, X., Kelemen, A. (2005) “Differential and Trajectory Methods for Time Course Gene Expression Data”. Bioinformatics 20(13): 3009-3016.
  • Liang, Y., Kelemen, A. (2005) “Temporal Gene Expression Classification with Regularised Neural Network”. International Journal of Bioinformatics Research and Applications 1(4), 399-413.
  • Kelemen, A., Liang, Y. (2005) "Optimizing Decision Making with Neural Network in Software Agents", WSEAS Transactions on Simulation Modeling and Optimization, pp. 256-261.
  • Liang, Y., Kelemen, A. (2004) “Hierarchical Bayesian Neural Network for Gene Expression Temporal Patterns”, Journal of Statistical Applications in Genetics and Molecular Biology 3(1), 1-23. http://www.bepress.com/sagmb/vol3/iss1/art20
  • Kelemen, A., Liang, Y., Kozma, R., and Franklin, S. (2002) "Optimizing Intelligent Agent's Constraint Satisfaction with Neural Networks", in: "Innovations in Intelligent Systems" (A. Abraham, L. Jain, J. Kacprzyk, Eds.), in the Series "Studies in Fuzziness and Soft Computing", Springer-Verlag, Heidelberg, Germany, pp. 255-272.
  • Kelemen, A., Liang Y. and Franklin, S. (2002) “A Comparative Study of Different Machine Learning Approaches for Decision Making”, in: “Recent Advances in Simulation, Computational Methods and Soft Computing” (N. E. Mastorakis, ed.) in the “Electrical and Computer Engineering Series”, WSEAS Press, Piraeus, Greece, 181-186.
  • Liang, Y., Lin, K., and Kelemen, A. (2002) "Adaptive Generalized Estimation Equation with Bayes Classifier for the Job Assignment Problem", in: "Advances in Knowledge Discovery and Data Mining" (M. Chen, P. S. Yu, B. Liu, Eds.) in the "Lecture Notes In Artificial Intelligence Series", Springer-Verlag, Heidelberg, Germany, pp. 438-450.
  • Franklin, S., Kelemen, A., and McCauley, L. (1998) “IDA: A Cognitive Agent Architecture”, in IEEE Systems Man and Cybernetics, IEEE Press, pp. 2646-2651.

Books

  • Kelemen, A., Abraham, A., Chen, Y. (2008) “Computational Intelligence in Bioinformatics” in the Series in Studies in Computational Intelligence, Springer-Verlag, Germany, Vol. 94, ISBN: 978-3-540-76802-9, 330 pages
  • Kelemen, A., Abraham, A., Liang, Y. (2008) “Computational Intelligence in Medical Informatics” in the Series in Studies in Computational Intelligence, Springer-Verlag, Germany, ISBN: 978-3-540-75766-5, 390 pages

Primary Teaching Areas

  • NURS 405: An Introduction to Informatics in Nursing and Health Care
  • NURS 418: Climate Change: Evidence and Solutions
  • NRSG 720: The Changing World of Informatics in Health Care
  • NURS 736: Technology Solutions for Knowledge Generation in Healthcare
  • NURS 770: Human Factors and Human-Computer Interaction
  • NURS 785: Health Care Database Systems
  • NURS 786: Systems Analysis and Design 
  • NDNP 807: Information Systems and Technology for the Improvement and Transformation of Health Care

Academic & Professional Activities

Editor:
International Journal of Computational Intelligence ResearchInternational Journal of Hybrid Intelligent SystemsInternational Journal of Computational Intelligence in Bioinformatics and Systems Biology

Scientific Review Committee: 
Science Center programs of the U.S. Department of State;NSF: Intelligent Information Systems;NIH: Emerging Technologies and Training in Neurosciences;NIH Challenge Grants;UMB-UMBC Partnership Grants; UMB-UMCP Seed Grants

Conference Organizer: 
International Conference on Intelligent Systems Design and Applications; Atlantic Symposium on Computational Biology & Genome Information; Summer Institute in Nursing Informatics; World Congress on Information and Communication Technologies; International Conference on Soft Computing and Pattern Recognition; World Congress on Nature and Biologically Inspired Computing; Intelligent Systems Design and Applications; Hybrid Intelligent Systems

Professional Memberships:
Science Advisory Board member at scienceboard.net; Union of Concerned Scientists; American Medical Informatics Association; Hungarian Academy of Sciences; Phi Kappa Phi Academic Honor; Upsilon Pi Epsilon Academic Honor Society for Computing Sciences; IEEE; American Mathematical Society; Hungarian Operations Research Society; Bolyai Janos Mathematical Society; International Mensa

Reviewer: 
International Journal of Hybrid Intelligent Systems, International Journal of Computational Intelligence Research, Journal of Bioinformatics, Journal of IEEE Transactions on Systems, Man and Cybernetics, Journal of IEEE Transactions on Neural Networks, Journal of Neural Computing & Applications, Journal of Fuzzy Sets and Systems, Journal of Expert Systems, Journal of BMC Bioinformatics, International Journal of Bioinformatics Research and Applications, Journal of Statistical Application in Genetics and Computational Biology, Journal of Neurocomputing, Journal of Hybrid Evolutionary Systems

Media Coverage: