See Google Scholar for recent papers.

107. A novel personalized random forest algorithm for clinical outcome prediction.
Johnson A, Cooper GF, Visweswaran S.
Virtual MedInfo Symposium. October 2021.
(paper)

106. The National COVID Cohort Collaborative (N3C) Rationale, design, infrastructure, and deployment.
Haendel MA, Chute CG, Bennett TD, Eichmann DA, Guinney J, Kibbe WA, Payne PRO, Pfaff ER, Robinson PN, Saltz JH, Spratt H, Suver C, Wilbanks J, Wilcox AB, Williams AE, Wu C, Blacketer C, Bradford RL, Cimino JJ, Clark M, Colmenares EW, Francis PA, Gabriel D, Graves A, Hemadri R, Hong SS, Hripscak G, Jiao D, Klann JG, Kostka K, Lee AM, Lehmann HP, Lingrey L, Miller RT, Morris M, Murphy SN, Natarajan K, Palchuk MB, Sheikh U, Solbrig H, Visweswaran S, Walden A, Walters KM, Weber GM, Zhang XT, Zhu RL, Amor B, Girvin AT, Manna A, Qureshi N, Kurilla MG, Michael SG, Portilla LM, Rutter JL, Austin CP, Gersing KR, N3C Consortium.
JAMIA. 2020.
(abstract & paper)

105. Hyperbolic molecular representation learning for drug repositioning.
Yu K, Visweswaran S, Batmanghelich K.
Machine Learning for Molecules 2020 workshop at NeurIPS 2020.
(abstract & paper)

104. Patient-specific modeling with personalized decision paths.
Johnson A, Cooper GF, Visweswaran S.
Virtual AMIA Fall Symposium. November 2020.
(paper)

103. Semi-supervised hierarchical drug embedding in hyperbolic space.
Yu K, Visweswaran S, Batmanghelich K.
Journal of Chemical Information and Modeling. 2020.
(abstract)

102. How high-risk comorbidities co-occur in readmitted patients with hip fracture: Big data visual analytical approach.
Bhavnani SK, Dang B, Penton R, Visweswaran S, Bassler KE, Chen T, Raji M, Divekar R, Zuhour R, Karmarkar A, Kuo Y-F, Ottenbacher KJ.
JMIR Medical Informatics. 2020;8(10):e13567.
(paper)

101. Exploring novel graphical presentations of clinical data in a Learning Electronic Medical Record.
Calzoni L, Clermont G, Cooper GF, Visweswaran S, Hochheiser H.
Applied Clinical Informatics, 11 (2020) 680-691.
(abstract)

100. Machine learning classifiers for Twitter surveillance of vaping: Comparative machine learning study.
Visweswaran S, Colditz JB, O’Halloran P, Han NR, Taneja SB, Welling J, Chu KH, Sidani JE, Primack BA.
Journal of Medical Internet Research. 2020;22(8):e17478.
(paper)

99. Leveraging eye tracking to prioritize relevant medical record data: Comparative machine learning study.
King AJ, Cooper GF, Clermont G, Hochheiser H, Hauskrecht M, Sittig DF, Visweswaran, S.
Journal of Medical Internet Research. 2020;22(4):e15876.
(paper)

98. An empirical investigation of instance-specific causal Bayesian network learning.
Jabbari F, Visweswaran S, Cooper GF.
Causal Analytics for Bioinformatics and Biomedicine (CABB) workshop in IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2019).
(paper)

97. Using machine learning to selectively highlight patient information.
King AJ, Cooper GF, Clermont G, Hochheiser H, Hauskrecht M, Sittig DF, Visweswaran, S.
Journal of Biomedical Informatics. 2019 Oct 29:103327.
(abstract)

96. Patient-specific explanations for predictions of risk outcomes.
Tajgardoon M, Samayamuthu M, Calzoni L, Visweswaran, S.
ACI Open. 2019; 03(02): e88-e97.
(abstract & paper)

95. Estimating and controlling the False Discovery Rate of the PC algorithm using edge-specific p-values.
Strobl EV, Spirtes P, Visweswaran, S.
ACM Transactions on Intelligent Systems and Technology. 2019 Oct 10;10(5):46.
(paper)

94. Dirac delta regression: Conditional density estimation with clinical trials.
Strobl EV, Visweswaran, S.
arXiv preprint arXiv:1905.10330, 2019.
(abstract & paper)

93. Interactive NLP in clinical care: Identifying incidental findings in radiology reports.
Trivedi G, Dadashzadeh E, Handzel R, Chapman W, Visweswaran, S, Hochheiser H.
Applied Clinical Informatics. 2019; 10(04): 655-669.
(abstract)

92. Identifying incidental findings from radiology reports of trauma patients: An evaluation of automated feature representation methods.
Trivedi G, Hong C, Dadashzadeh E, Handzel R, Hochheiser H, Visweswaran, S.
International Journal of Medical Informatics. 2019 Sep 1;129:81-7.
(abstract)

91. The “All of Us” Research Program.
All of Us Research Program Investigators.
New England Journal of Medicine. 2019 Aug 15;381(7):668-76.
(abstract)

90. Derivation, validation, and potential treatment implications of novel clinical phenotypes for sepsis.
Seymour CW, Kennedy J, Wang S, Chang C-CH, Elliot CF, Xu Z, Berry S, Clermont G, Cooper G, Gomez H, Huang DT, Kellum JA, Mi Q, Opal SM, Talisa V, Poll T, Visweswaran S, Vodovotz Y, Weiss JC, Yealy DM, Yende S, Angus DC.
JAMA. 2019 May 28;321(20):2003-17.
(paper)

89. 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.
(abstract & paper)

88. 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.
(abstract & paper)

87. 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.
(abstract & paper)

86. 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.
(abstract & paper)

85. 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.
(abstract & paper)

84. 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.
(Outstanding Paper Award at the Science of Team Science (SciTS) Conference, 2018)
(presentation)

83. 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.
(Awarded First Place in the Student Paper Competition at the AMIA Informatics Summit Clinical Research Informatics, 2018)
(paper)

82. 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 Aug; 6(1):47-62.
(paper)

81. 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. 2019 May 21;20(3):842-856.
(abstract) (paper)

80. 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. 2018 Jul 26;46(5):509-521.
(abstract) (paper)

79. 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.
(abstract) (paper)

78. 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.
(abstract) (paper)

77. 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.
(abstract) (paper)

76. 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.
(Awarded First Place in the Student Paper Competition at the AMIA Joint Summits Clinical Research Informatics, 2017)
(abstract) (paper)

75. Learning parsimonious classification rules from gene expression data using Bayesian networks with local structure.
Lustgarten JL, Balasubramanian JB, Visweswaran S, Gopalakrishnan V.
Data. 2017 Mar;2(1).
(abstract) (paper)

74. 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.
(abstract) (paper)

73. 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.
(abstract) (paper)

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.
(abstract) (paper)

71. Markov boundary discovery with ridge regularized linear models.
Strobl EV, Visweswaran S.
Journal of Causal Inference. 2016 Mar; 4(1):31-48.
(abstract) (paper)

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.
(Awarded First Place in the Student Paper Competition at the AMIA Annual Symposium, 2015)
(abstract) (paper)

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.
(abstract) (paper)

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.
(abstract) (paper)

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.
(paper)

66. Personalized modeling for prediction with decision-path models.
Visweswaran S, Ferreira A, Cooper, GF.
PLoS One. 2015 Jun 22;10(6):e0131022.
(abstract) (paper)

65. KNGP: A network-based gene prioritization algorithm that incorporates multiple sources of knowledge.
Kimmel C, Visweswaran S.
American Journal of Bioinformatics and Computational Biology. 2015 Apr 25; 3(1):1-4.
(paper)

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.
(abstract) (paper)

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.
(abstract) (paper)

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.
(abstract) (paper)

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.
(abstract) (paper)

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.
(abstract) (paper)

59. Informative Bayesian Model Selection: A method for identifying interactions in genome-wide data.
Aflakparast M, Masoudi-Nejad A, Bozorgmehr JH, Visweswaran S.
Molecular BioSystems, 2014 Aug;10(10):2654-62.
(abstract) (paper)

58. Dependence versus conditional dependence in local causal discovery from gene expression data.
Strobl EV, Visweswaran S.
arXiv preprint arXiv:1407.7566, 2014.
(abstract & paper)

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.
Heredity. 2014 Jun;112(6):666-74.
(abstract) (paper)

56. Counting Markov blankets.
Visweswaran S, Cooper GF.
arXiv preprint arXiv:1407.2483, 2014.
(abstract & paper)

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.
(abstract) (abstract)

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.
(abstract) (paper)

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.
(abstract) (paper)

52. Markov blanket discovery using kernel-based conditional dependence measures.
Strobl EV, Visweswaran S.
In: Proceedings of the NIPS 2013 Workshop on Causality, Lake Tahoe, NV. 2013 Dec.

51. Deep multiple kernel learning.
Strobl EV, Visweswaran S.
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.
Kimmel C, Visweswaran S.
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.
Hauskrecht M, Visweswaran S, Cooper GF, Clermont G.
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.
Stokes M, Visweswaran S.
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.
Lustgarten JL*, Visweswaran S*, Gopalakrishnan V, Cooper GF. *Co-first authors
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, 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.
Visweswaran S, Cooper GF.
Journal of Machine Learning Research. 2010 Dec 1; 11:3369-3405.
(abstract)

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.
(abstract)

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.
(abstract)

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.
(abstract)

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.
(abstract)

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.
(abstract)

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.
(abstract)

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.
(abstract)

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.
(abstract)

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.
(abstract)

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.
(abstract)

20. Gene prioritization using a probabilistic knowledge model: A case study in Alzheimer’s disease.
Wang S, Hauskrecht M, Visweswaran S.
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.
(abstract)

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.
(abstract)

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.
(abstract)

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.
(abstract)

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.
(abstract)

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.
(abstract)

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.
(abstract)

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.
(abstract)

7. Patient-specific models for predicting the outcomes of patients with community acquired pneumonia.
Visweswaran S, Cooper GF.
In: AMIA Annual Symposium Proceedings. 2005 Oct 22-26; 2005:759-63.
(abstract)

6. Deriving the expected utility of a predictive model when the utilities are uncertain.
Cooper GF, Visweswaran S.
In: AMIA Annual Symposium Proceedings. 2005 Oct 22-26; 2005:161-5.
(abstract)

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.
(abstract)

4. Instance-specific Bayesian model averaging for classification.
Visweswaran S, Cooper GF.
In: Advances in Neural Information Processing Systems (NIPS 2004). 2004 Dec 13-18:1449-56.
(paper)

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.
(abstract)

2. Retrieval and classification of dental research articles.
Bartling WC, Schleyer TK, Visweswaran S.
Advances in Dental Research. 2003 Dec; 17:115-20.
(abstract)

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.
(abstract)

6. Risk stratification and prognosis using predictive modelling and big data approaches.
Visweswaran S, Cooper GF.
In Adam T and Aliferis C (Eds): Personalized and Precision Medicine Informatics: A Workflow-Based View. Springer; 2020.
(book)

5. Markov blanket ranking using kernel-based conditional dependence measures.
Strobl EV, Visweswaran S.
In Guyon I, Statnikov A and Batu BB (Eds): Cause Effect Pairs in Machine Learning. Springer International Publishing; 2019.
(book)

4. Prediction of clinical outcomes from genome-wide data.
Visweswaran S.
In Sinoquet, C and Mourad, R (Eds): Probabilistic Graphical Models for Genetics, Genomics and Postgenomics, Oxford University Press, UK, 2014.
(book)

3. Scoring, searching, and evaluating Bayesian network models of gene-phenotype association.
Jiang X, Visweswaran S, Neapolitan RE.
In Sinoquet, C and Mourad, R (Eds): Probabilistic Graphical Models for Genetics, Genomics and Postgenomics, Oxford University Press, UK, 2014.
(book)

2. Learning genetic epistasis using Bayesian network scoring criteria.
Jiang X, Neapolitan RE, Barmada MM, Visweswaran S.
In Liu (Ed): Bioinformatics: The Impact of Accurate Quantification on Proteomic and Genetic Analysis and Research, Apple Academic Press, 2014.
(book)

1. Mining epistatic interactions from high-dimensional data sets using Bayesian networks.
Jiang X, Visweswaran S, Neapolitan RE.
In Holmes, D and Jain, L (Eds): Foundations and Intelligent Paradigms–3, Springer-Verlag, Berlin Heidelberg, 2011.
(book)

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, Bassler KE.
System demonstration; In: Symposium of the American Medical Informatics Association. 2017 Nov 7.
(abstract)

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.
In: AMIA Joint Summits Translational Science Proceedings. 2015 Mar 23; 2015.
(abstract)