Source: http://www.thevislab.com/lab/doku.php?id=publications
Timestamp: 2019-04-23 10:40:36+00:00

Document:
90. Approximate kernel-based conditional independence tests for fast non-parametric causal discovery.
Strobl, EV, Zhang, K, Visweswaran, S.
Journal of Causal Inference. 2019 Mar; 4(1):31-48.
89. Towards team-centered informatics: Accelerating innovation in multidisciplinary scientific teams through visual analytics.
Bhavnani SK, Visweswaran S, Divekar R, Brasier A.
The Journal of Applied Behavioral Science. 2019 Mar;55(1):50-72.
88. Using machine learning to predict the information seeking behavior of clinicians using an electronic medical record system.
King, AJ, Cooper, GF, Hochheiser, H, Clermont, G, Hauskrecht, M, Visweswaran, S.
In: AMIA Annual Symposium Proceedings. 2018 Nov 7.
87. Instance-specific Bayesian network structure learning.
Jabbari F, Visweswaran S, Cooper GF.
In: The 9th International Conference on Probabilistic Graphical Models. 2018 Sep 11 – 14.
86. Accrual to Clinical Trials (ACT): A Clinical and Translational Science Award Consortium network.
Visweswaran S, Becich MJ, D’Itri VS, Sendro ER, MacFadden D, Anderson NR, Allen KA, Ranganathan D, Murphy SN, Morrato EH, Pincus HA, Toto R, Firestein GS, Nadler LM, Reis SE.
JAMIA Open. 2018 Aug 21.
85. Accelerating innovation in multidisciplinary scientific teams through visual analytics.
Bhavnani, SK, Visweswaran, S, Divekar, R.
In: Science of Team Science (SciTS) Conference. 2018 May 21-24.
84. A novel representation of vaccine efficacy trial datasets for use in computer simulation of vaccination policy.
Tajgardoon, M, Wagner, MM, Visweswaran, S, Zimmerman, RK.
In: AMIA Informatics Summit Proceedings. 2018 Mar 12-15.
83. Fast causal inference with non-random missingness by test-wise deletion.
Strobl, EV, Visweswaran, S, Spirtes, PL.
International Journal of Data Science and Analytics. 2018 Jan 9.
82. Translational bioinformatics in mental health: Open access data sources and computational biomarker discovery.
Tenenbaum, JD, Bhuvaneshwar, K, Gagliardi, JP, Hollis, KF, Jia, P, Ma, L, Nagarajan, R, Rakesh, G, Subbian, V, Visweswaran, S, Zhao, Z, Rozenblit, L.
Briefings in Bioinformatics. 2017 Nov 27.
81. Methylation differences reveal heterogeneity in preterm pathophysiology: results from bipartite network analyses.
Bhavnani SK, Dang B, Kilaru V, Caro M, Visweswaran S, Saade G, Smith AK, Menon R.
Journal of Perinatal Medicine. 2017 Jun 30.
80. Automated annotation and classification of BI-RADS assessment from radiology reports.
Castro, SM, Tseytlin, E, Medvedeva, O, Mitchell, K, Visweswaran, S, Bekhuis, T, Jacobson, RS.
Journal of Biomedical Informatics. 2017 May;69:177-187.
79. The building blocks of interoperability: A multisite analysis of patient demographic attributes available for matching.
Culbertson, A, Goel, S, Madden, M, Safaeinili, N, Jackson, KL, Carton, T, Waitman, R, Liu, M, Krishnamurthy, A, Hall, L, Cappella, N, Visweswaran, S, Becich, MJ, Applegate, R, Bernstam, E, Rothman, R, Matheny, M, Lipori, G, Bian, J, Hogan, W, Bell, D, Martin, A, Grannis, S, Klann, J, Sutphen, R, O'Hara, AB, Kho, A.
Applied Clinical Informatics. 2017 Apr 5;8(2):322-336.
78. Enabling comprehension of patient subgroups and characteristics in large bipartite networks: Implications for precision medicine.
Bhavnani, SK, Chen, T, Ayyaswamy, A, Visweswaran, S, Bellala, G, Divekar, R, Bassler, KE.
In: AMIA Joint Summits Translational Science Proceedings. 2017 Mar 27-30; 2017:21-29.
77. Eye-tracking for clinical decision support: A method to capture automatically what physicians are viewing in the EMR.
King, AJ, Hochheiser, H, Visweswaran, S, Clermont, G, Cooper, GF.
In: AMIA Joint Summits Translational Science Proceedings. 2017 Mar 27-30; 2017:512-21.
76. Learning parsimonious classification rules from gene expression data using Bayesian networks with local structure.
Lustgarten, JL, Balasubramanian, JB, Visweswaran, S, Gopalakrishnan, V.
75. Outlier-based detection of unusual patient-management actions: An ICU study.
Hauskrecht, M, Batal, I, Hong, C, Cooper, GF, Viswewaran, S, Clermont, G.
Journal of Biomedical Informatics. 2016 Dec;64:211-221.
74. An informatics research agenda to support precision medicine: 7 key areas.
Tenenbaum, JD, Avillach, P, Benham-Hutchins, M, Breitenstein, MK, Crowgey, EL, Hoffman, MA, Jiang, X, Madhavan, S, Mattison, JE, Radhakrishnan, N, Ray, B, Shin, D, Visweswaran, S, Zhao, Z, Freimuth, RR.
Journal of the American Medical Informatics Association. 2016 Jul;23(4):791-5.
73. Estimating and controlling the False Discovery Rate for the PC algorithm using edge-specific p-values.
Strobl, EV, Spirtes, PL, Visweswaran, S.
72. On predicting lung cancer subtypes using ‘omic’data from tumor and tumor-adjacent histologically-normal tissue.
Pineda, AL, Ogoe, HA, Balasubramanian, JB, Escareño, CR, Visweswaran, S, Herman, JG, Gopalakrishnan, V.
BMC Cancer. 2016 Mar 4;16(1):184.
71. Markov boundary discovery with ridge regularized linear models.
Journal of Causal Inference. 2016 Mar; 4(1):31-48.
70. Development and preliminary evaluation of a prototype of a learning electronic medical record system.
King, AJ, Cooper, GF, Hochheiser, H, Clermont, G, Visweswaran, S.
In: AMIA Annual Symposium Proceedings. 2015 Nov 17; 2015:1967-75.
69. Comparison of machine learning classifiers for influenza detection from emergency department free text reports.
Pineda, AL, Ye, Y, Visweswaran, S, Cooper, GF, Wagner, MM, Tsui, FC.
Journal of Biomedical Informatics. 2015 Sep 16. pii: S1532-0464(15)00187-2.
68. Knowledge transfer via classification rules using functional mapping for integrative modeling of gene expression data.
Ogoe, HA, Visweswaran, S, Lu, X, Gopalakrishnan, V.
BMC Bioinformatics. 2015 Jul 23; 16:226.
67. Patient-specific modeling of medical data.
Ribeiro, GAS, Oliveira, ACM, Ferreira, ALS, Visweswaran, S, Cooper, GF.
In: Proceedings of the Machine Learning and Data Mining in Pattern Recognition: 11th International Conference, MLDM 2015. Hamburg, Germany, Jul 20-21, 2015.
66. Personalized modeling for prediction with decision-path models.
Visweswaran, S, Ferreira, A, Cooper, GF.
PLoS One. 2015 Jun 22;10(6):e0131022.
65. KNGP: A network-based gene prioritization algorithm that incorporates multiple sources of knowledge.
American Journal of Bioinformatics and Computational Biology. 2015 Apr 25; 3(1):1-4.
64. How comorbidities co-occur in readmitted hip fracture patients: From bipartite networks to insights for post-discharge planning.
Bhavnani, SK, Bryant, D, Visweswaran, S, Divekar, R, Karmarkar, A, Ottenbacher, K.
In: AMIA Joint Summits Translational Science Proceedings. 2015 Mar 23; 2015.
63. Unlocking proteomic heterogeneity in complex diseases through visual analytics.
Bhavnani, SK, Dang, B, Bellala, G, Divekar, R, Visweswaran, S, Brasier, A, Kurosky, A.
Proteomics. 2015 Feb 13; 15(8):1405-18.
62. Identifying genetic interactions associated with late-onset Alzheimer's disease.
Floudas, CS, Kamboh, MI, Barmada, MM, Visweswaran S.
BioData Mining. 2014 Dec 19; 7(1):35.
61. Semi-automated literature mining to identify putative biomarkers of disease from multiple biofluids.
Jordan, R, Visweswaran S, Gopalakrishnan, V.
Journal of Clinical Bioinformatics. 2014 Oct 23;4:13.
60. Evaluation of a four-protein biomarker panel for detection of esophageal adenocarcinoma.
Zaidi, AH, Gopalakrishnan, V, Kasi, PM, Malhotra, U, Balasubramanian, J, Visweswaran S, Zeng, X, Sun, M, Bergman, JJ, Bigbee, WL, Jobe, BA.
Cancer. 2014 Dec 15; 120(24):3902-13.
59. Informative Bayesian Model Selection: A method for identifying interactions in genome-wide data.
Aflakparast, M, Masoudi-Nejad, A, Bozorgmehr, JH, Visweswaran S.
58. Dependence versus conditional dependence in local causal discovery from gene expression data.
57. Cuckoo search epistasis: A new method for exploring significant genetic interactions.
Aflakparast, M, Salimi, H, Gerami, A, Dube, M-P, Visweswaran S, Masoudi-Nejad, A.
55. The application of network label propagation to rank biomarkers in genome-wide Alzheimer's data.
Stokes, ME, Barmada, MM, Kamboh, MI, Visweswaran S.
BMC Genomics. 2014 Apr 14;15(1):282.
54. Selective model averaging with Bayesian rule learning for predictive biomedicine.
Balasubramanian, JB, Visweswaran S, Cooper, GF, Gopalakrishnan, V.
In: AMIA Joint Summits Translational Science Proceedings. 2014 Apr 7; 2014:17-22.
53. Heterogeneity within and across pediatric pulmonary infections: From bipartite networks to at-risk subphenotypes.
Bhavnani, SK, Dang, B, Caro, M, Bellala, G, Visweswaran S, Asuncion, M, Divekar, R.
In: AMIA Joint Summits Translational Science Proceedings (Apr 2014). 2014 Apr 7; 2014:29-34.
52. Markov blanket discovery using kernel-based conditional dependence measures.
In: Proceedings of the NIPS 2013 Workshop on Causality, Lake Tahoe, NV. 2013 Dec.
51. Deep multiple kernel learning.
In: Proceedings of the 12th International Conference on Machine Learning and Applications (ICMLA'13). 2013 Dec 4; 2013:414-17.
50. An algorithm for network-based gene prioritization that encodes knowledge both in nodes and in links.
PLoS One. 2013 Nov 19; 8(11):e79564.
49. Data-driven identification of unusual clinical actions in the ICU.
Hauskrecht, M, Visweswaran, S, Cooper, GF, Clermont, G.
In: AMIA Annual Symposium Proceedings. 2013 Nov 16; 2013.
48. Decision path models for patient-specific modeling of patient outcomes.
Ferreira, A, Cooper, GF, Visweswaran, S.
In: AMIA Annual Symposium Proceedings. 2013 Nov 16; 2013:413-21.
47. Conditional outlier approach for detection of unusual patient care actions.
In: Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence. 2013 Jul 14; 2013.
46. Detection of patients with influenza syndrome using machine-learning models learned from Emergency Department reports.
Pineda AL, Tsui FC, Visweswaran, S, Cooper GF.
Online Journal of Public Health Informatics. 2013 Apr 4; 5(1):e41.
45. How cytokines co-occur across rickettsioses patients: From bipartite visual analytics to mechanistic inferences of a cytokine storm.
Bhavnani, SK, Drake, J, Bellala, G, Dang, B, Peng, B, Oteo, JA, Santibañez-Saenz, P, Visweswaran, S, Olano, JP.
In: AMIA Joint Summits Translational Science Proceedings. 2013 Mar 18; 2013:15-9.
44. Noninvasive predictors of subdural grid seizure localization in children with nonlesional focal epilepsy.
Kalamangalam, GP, Pestana Knight, EM, Visweswaran, S, Gupta, A.
Journal of Clinical Neurophysiology. 2013 Feb; 30(1):45-50.
43. Outlier detection for patient monitoring and alerting.
Hauskrecht, M, Batal, I, Valko, M, Visweswaran, S, Cooper, GF, Clermont, G.
Journal of Biomedical Informatics. 2013 Feb; 46(1):47-55.
42. Application of a spatially-weighed Relief algorithm for ranking genetic predictors of disease.
BioData Mining. 2012 Dec 3; 5(1):20.
41. Predicting the risk of psychosis onset: Advances and prospects.
Strobl, EV, Eack, SM, Swaminathan, V, Visweswaran, S.
Early Intervention in Psychiatry. 2012 Nov;6(4):368-79.
40. The role of complementary bipartite visual analytical representations in the analysis of SNPs: A case study in ancestral informative markers.
Bhavnani, SK, Bellala, G, Victor, S, Bassler, K, Visweswaran, S.
Journal of the American Medical Informatics Association. 2012 Jun 1; 19(e1):e5-e12.
39. Building an automated SOAP classifier for emergency department reports.
Mowery, D, Weibe, J, Visweswaran, S, Harkema, H, Chapman, WW.
Journal of Biomedical Informatics. 2012 Feb; 45(1):71-81.
38. A multivariate probabilistic method for comparing two clinical datasets.
Sverchkov, Y, Visweswaran, S, Clermont, G, Hauskrecht, M, Cooper, GF.
In: Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium. 2012 Jan 28; 2012:795-800.
37. Application of an efficient Bayesian discretization method to biomedical data.
BMC Bioinformatics. 2011 Jul 28; 12:309.
36. Computerized detection of adverse drug reactions in the medical intensive care unit.
Kane-Gill, SL, Visweswaran, S, Saul, MI, Wong, AI, Penrod, L, Handler, SM.
International Journal of Medical Informatics. 2011 Aug; 80(8):570-8.
35. The application of naive Bayes model averaging to predict Alzheimer’s disease from genome-wide data.
Wei, W, Visweswaran, S, Cooper, GF.
Journal of the American Medical Informatics Association. 2011 Jul-Aug; 18(4):370-5.
34. Identifying interacting environmental factor – gene pairs.
Kimmel, C, Lustgarten, J, Handler, SM, Wong, AI, Visweswaran, S.
In: Proceedings of the 5th International Symposium on Bio- and Medical Informatics and Cybernetics (BMIC 2011). 2011 Jul 19; 2011.
33. Learning genetic epistasis using Bayesian network scoring criteria.
Jiang, X, Neapolitan, RE, Barmada, MM, Visweswaran, S.
BMC Bioinformatics. 2011 Mar 31; 12:89.
32. Learning instance-specific predictive models.
Journal of Machine Learning Research. 2010 Dec 1; 11:3369-3405.
31. Identifying deviations from usual medical care using a statistical approach. Visweswaran, S, Mezger, J, Clermont, G, Hauskrecht, M, Cooper, GF.
In: AMIA Annual Symposium Proceedings. 2010 Nov 13; 2010:827-31.
30. Conditional outlier detection for clinical alerting.
Hauskrecht, M, Valko, M, Batal, I, Clermont, G, Visweswaran, S, Cooper, GF.
In: AMIA Annual Symposium Proceedings. 2010 Nov 13; 2010:286-90.
29. An efficient Bayesian method for predicting clinical outcomes from genome-wide data.
Cooper, GF, Hennings-Yeomans, P, Visweswaran, S, Barmada, MM.
In: AMIA Annual Symposium Proceedings. 2010 Nov 13; 2010:127-31.
28. A fast algorithm for learning epistatic genomic relationships.
Jiang, X, Neapolitan, RE, Barmada, MM, Visweswaran, S, Cooper, GF.
In: AMIA Annual Symposium Proceedings. 2010 Nov 13; 2010:341-5.
27. The use of semantic distance metrics to support ontology.
Wang, J, Day, R, Visweswaran, S, Hogan, W.
In: AMIA Annual Symposium Proceedings. 2010 Nov 13; 2010:842-6.
26. Identifying genetic Interactions in genome-wide data using Bayesian networks.
Jiang, X, Barmada, MM, Visweswaran, S.
Genetic Epidemiology. 2010 Sep; 34(6):575-81.
25. Learning patient-specific predictive models from clinical data.
Visweswaran, S, Angus, DC, Hsieh, M, Weissfeld, L, Yealy, D, Cooper, GF.
Journal of Biomedical Informatics. 2010 Oct; 43(5):669-85.
24. Candidate gene prioritization using network based probabilistic models.
Wang, S, Hauskrecht, M, Visweswaran, S.
In: Proceedings of the AMIA Summit on Translational Bioinformatics. 2010.
23. Bayesian rule learning for biomedical data mining.
Gopalakrishnan, V, Lustgarten, JL, Visweswaran, S, Cooper, GF.
Bioinformatics. 2010 Mar 1; 26(5):668-75.
22. Measuring stability of feature selection in biomedical datasets.
Lustgarten, JL, Gopalakrishnan, V, Visweswaran, S.
In: AMIA Annual Symposium Proceedings. 2009 Nov 14; 2009:406-10.
21. A Bayesian method for identifying genetic interactions.
Visweswaran, S, Wong, AI, Barmada, MM.
In: AMIA Annual Symposium Proceedings. 2009 Nov 14; 2009:673-7.
20. Gene prioritization using a probabilistic knowledge model: A case study in Alzheimer’s disease.
In: Proceedings of the IEEE-BIBM Workshop on Graph Techniques for Biomedical Networks. 2009 Nov 1; 2009.
19. Learning probabilistic knowledge model for document retrieval.
Wang, S, Visweswaran, S, Hauskrecht, M.
In: Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (KDIR). 2009 Oct 6; 2009:60-71.
18. Noninvasive correlates of subdural grid electrographic outcome.
Kalamangalam, GP, Morris, HH, Mani, J, Lachhwani, DK, Visweswaran, S, Bingaman, WM.
Journal of Clinical Neurophysiology. 2009 Oct; 26(5):333-41.
17. Knowledge-based variable selection for rule learning on proteomic data.
Lustgarten, JL, Visweswaran, S, Bowser, RP, Hogan, WR, Gopalakrishnan, V.
BMC Bioinformatics. 2009 Sep 17; 10 Suppl 9:S16.
16. Assessing the quality of prescribing and monitoring erythropoiesis stimulating agents in the nursing home setting.
Wong, AI, Stephens, SB, Aspinall, MB, Visweswaran, S, Hanlon, JT, Handler, SM.
Journal of the American Medical Directors. 2009 Jul; 10(6):436-9.
15. Improving a knowledge base for use in proteomic data analysis.
Lustgarten, JL, Gopalakrishnan, V, Hogan, WR, Visweswaran, S.
In: Proceedings of the Intelligent Data Analysis in Medicine And Pharmacology (IDAMAP-08). 2008 Nov 7; 2008:87-89.
14. Analysis of a failed clinical decision support system for management of congestive heart failure.
Wadhwa, R, Fridsma, DB, Saul, MI, Penrod, LE, Visweswaran, S, Cooper, GF, Chapman, W.
In: AMIA Annual Symposium Proceedings. 2008 Nov 6; 2008:773-7.
13. Assessing the performance characteristics of signals used by a clinical event monitor to detect adverse drug reactions in the nursing home.
Handler, SM, Hanlon, JT, Perera, S, Saul, MI, Fridsma, DB, Visweswaran, S, Studenski, SA, Roumani, YF, Castle, NG, Nace, DA, Becich, MJ.
In: AMIA Annual Symposium Proceedings. 2008 Nov 6; 2008:278-82.
12. Improving classification performance with discretization on biomedical datasets.
Lustgarten, JL, Gopalakrishnan, V, Grover, H, Visweswaran, S.
In: AMIA Annual Symposium Proceedings. 2008 Nov 6; 2008:445-9.
11. Conditional anomaly detection methods for patient–management alert systems.
Valko, M, Cooper, GF, Seybert, A, Visweswaran, S, Saul, M, Hauskrecht, M.
In: Proceedings of the Workshop on Machine Learning in Health Care Applications in The Twenty-Fifth International Conference on Machine Learning. 2008 Jul 9; 2008.
10. An evaluation of discretization methods for learning rules from biomedical datasets.
Lustgarten, JL, Visweswaran, S, Grover, H, Gopalakrishnan, V.
In: Proceedings of the International Conference on Bioinformatics and Computational Biology (BIOCOMP-08). 2008 Jul 14; 2008:527-32.
9. Improving peptide identification via validation with intensity-based modeling of tandem mass spectra.
Grover, H, Lustgarten, JL, Visweswaran, S, Gopalakrishnan, V.
In: Proceedings of the International Conference on Bioinformatics, Computational Biology, Genomics and Chemoinformatics (BCBGC-08). 2008:56-63.
8. Evidence-based anomaly detection in clinical domains.
Hauskrecht, M, Valko, M, Kveton, B, Visweswaran, S, Cooper, GF.
In: AMIA Annual Symposium Proceedings. 2007 Oct 11; 2007:319-23.
7. Patient-specific models for predicting the outcomes of patients with community acquired pneumonia.
In: AMIA Annual Symposium Proceedings. 2005 Oct 22-26; 2005:759-63.
6. Deriving the expected utility of a predictive model when the utilities are uncertain.
In: AMIA Annual Symposium Proceedings. 2005 Oct 22-26; 2005:161-5.
5. Detection of very-high-level penicillin resistant variants of the Tennessee 23F-4 clone via single and serial transformations with four serotype 19A international pneumococcal clones.
McEllistrem, MC, Adams, JM, Visweswaran, S, Khan S.
Microbial Drug Resistance. 2005 Fall; 11(3):271-8.
4. Instance-specific Bayesian model averaging for classification.
In: Advances in Neural Information Processing Systems (NIPS 2004). 2004 Dec 13-18:1449-56.
3. Serotype 14 variants of the France 9V-3 Clone from Baltimore, Maryland can be differentiated by the cpsB gene.
McEllistrem, CM, Noller, AC, Visweswaran, S, Adams JM, Harrison, LH.
Journal of Clinical Microbiology. 2004 Jan; 42(1):250-6.
2. Retrieval and classification of dental research articles.
Bartling, WC, Schleyer, TK, Visweswaran, S.
Advances in Dental Research. 2003 Dec; 17:115-20.
1. Detecting adverse drug events in discharge summaries using variations on the simple Bayes model.
Visweswaran, S, Hanbury, P, Saul, M, Cooper, GF.
In: AMIA Annual Symposium Proceedings. 2003 Nov 8-12; 2003:689-93.
4. Prediction of clinical outcomes from genome-wide data.
In Sinoquet, C and Mourad, R (Eds): Probabilistic Graphical Models for Genetics, Genomics and Postgenomics, Oxford University Press, UK, 2014.
3. Scoring, searching, and evaluating Bayesian network models of gene-phenotype association.
Jiang X, Visweswaran, S, Neapolitan, RE.
2. Learning genetic epistasis using Bayesian network scoring criteria.
In Liu (Ed): Bioinformatics: The Impact of Accurate Quantification on Proteomic and Genetic Analysis and Research, Apple Academic Press, 2014.
1. Mining epistatic interactions from high-dimensional data sets using Bayesian networks.
In Holmes, D and Jain, L (Eds): Foundations and Intelligent Paradigms–3, Springer-Verlag, Berlin Heidelberg, 2011.
3. Vicinity exploration: Enabling user-driven visual search of multiple machine learning models for precision medicine.
Bhavnani, SK, Ayyaswamy, A, Chen, T, Visweswaran, S, Bellala, G, Kevin E. Bassler, KE.
System demonstration; In: Symposium of the American Medical Informatics Association. 2017 Nov 7.
2. Secondary use of data for research - EHR, omics and environmental data.
Visweswaran, S, Tenenbaum, J, Gouripeddi, R.
In: AMIA Joint Summits Translational Science Proceedings. 2016 Mar 22.
1. Where is the science in big data visual analytics? From pretty pictures to transformative biomedical discoveries.
Bhavnani, SK, Visweswaran, S, Divekar, R, Bellala, G.

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