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2010 – 2019
- 2017
[j14]Daniel Cannon, Jeremy J. Yang, Stephen L. Mathias, Oleg Ursu, Subramani Mani, Anna Waller
, Stephan C. Schürer, Lars Juhl Jensen, Larry A. Sklar, Cristian Bologa, Tudor I. Oprea:
TIN-X: target importance and novelty explorer. Bioinform. 33(16): 2601-2603 (2017)- [j13]Stuart J. Nelson, Tudor I. Oprea, Oleg Ursu, Cristian Bologa, Amrapali Zaveri, Jayme Holmes, Jeremy J. Yang, Stephen L. Mathias, Subramani Mani, Mark S. Tuttle, Michel Dumontier:
Formalizing drug indications on the road to therapeutic intent. J. Am. Medical Informatics Assoc. 24(6): 1169-1172 (2017) - [j12]Subramani Mani, Daniel Cannon, Robin Ohls, Tudor I. Oprea, Stephen L. Mathias, Karri Ballard, Oleg Ursu, Cristian Bologa:
Protein biomarker druggability profiling. J. Biomed. Informatics 66: 241-247 (2017) - [j11]Dac-Trung Nguyen, Stephen L. Mathias, Cristian Bologa, Søren Brunak, Nicolas F. Fernandez, Anna Gaulton, Anne Hersey, Jayme Holmes, Lars Juhl Jensen, Anneli Karlsson, Guixia Liu, Avi Ma'ayan, Geetha Mandava, Subramani Mani, Saurabh Mehta, John P. Overington, Juhee Patel, Andrew D. Rouillard, Stephan C. Schürer, Timothy Sheils, Anton Simeonov, Larry A. Sklar, Noel Southall, Oleg Ursu, Dusica Vidovic, Anna Waller, Jeremy J. Yang, Ajit Jadhav, Tudor I. Oprea, Rajarshi Guha:
Pharos: Collating protein information to shed light on the druggable genome. Nucleic Acids Res. 45(Database-Issue): D995-D1002 (2017) - 2016
- [c22]Subramani Mani, Daniel Cannon, Karri Ballard, Robin Ohls:
Protein Biomarker Discovery and Ranking for Early Detection of Necrotizing Enterocolitis in Neonates. AMIA 2016 - 2015
- [c21]Subramani Mani, Daniel Cannon, Tudor I. Oprea, Stephen L. Mathias, Oleg Ursu, Cristian Bologa:
Protein Drug Target Prioritization for Illumination. AMIA 2015 - 2014
- [j10]Subramani Mani, Asli Ozdas, Constantin F. Aliferis, Huseyin Atakan Varol, Qingxia Chen, Randy J. Carnevale, Yukun Chen, Joann Romano-Keeler, Hui Nian, Jörn-Hendrik Weitkamp:
Medical decision support using machine learning for early detection of late-onset neonatal sepsis. J. Am. Medical Informatics Assoc. 21(2): 326-336 (2014) - [c20]Subramani Mani, Joshua Swamidass, Noel Southall, Tudor I. Oprea:
Genomic dark matter, druggability and misunderstood targets. AMIA 2014 - 2013
- [j9]Subramani Mani, Yukun Chen, Xia Li, Lori R. Arlinghaus, A. Bapsi Chakravarthy, Vandana G. Abramson, Sandeep R. Bhave, Mia A. Levy, Hua Xu, Thomas E. Yankeelov:
Research and applications: Machine learning for predicting the response of breast cancer to neoadjuvant chemotherapy. J. Am. Medical Informatics Assoc. 20(4): 688-695 (2013) - 2012
- [j8]Yukun Chen, Subramani Mani, Hua Xu:
Applying active learning to assertion classification of concepts in clinical text. J. Biomed. Informatics 45(2): 265-272 (2012) - [c19]Subramani Mani, Yukun Chen, Tom Elasy, Warren Clayton, Joshua C. Denny:
Type 2 Diabetes Risk Forecasting from EMR Data using Machine Learning. AMIA 2012 - [i1]Subramani Mani, Peter Spirtes, Gregory F. Cooper:
A theoretical study of Y structures for causal discovery. CoRR abs/1206.6853 (2012) - 2011
- [j7]Min Jiang, Yukun Chen, Mei Liu, S. Trent Rosenbloom, Subramani Mani, Joshua C. Denny, Hua Xu:
A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries. J. Am. Medical Informatics Assoc. 18(5): 601-606 (2011) - [c18]Yukun Chen, Subramani Mani:
Active Learning for Unbalanced Data in the Challenge with Multiple Models and Biasing. Active Learning and Experimental Design @ AISTATS 2011: 113-126 - 2010
- [j6]Mei Liu, Joshua C. Denny, Subramani Mani, Yukun Chen, Yong Hu, Hua Xu:
Identifying potential drugs that induce QT prolongation using electronic medical records. BMC Bioinform. 11(S-4): P2 (2010) - [j5]Subramani Mani:
Letter: Note on Friedman's 'fundamental theorem of biomedical informatics'. J. Am. Medical Informatics Assoc. 17(5): 614 (2010) - [j4]Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos:
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation. J. Mach. Learn. Res. 11: 171-234 (2010) - [j3]Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos:
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions. J. Mach. Learn. Res. 11: 235-284 (2010) - [c17]Subramani Mani, Constantin F. Aliferis, Alexander R. Statnikov:
Bayesian Algorithms for Causal Data Mining. NIPS Causality: Objectives and Assessment 2010: 121-136
2000 – 2009
- 2009
- [c16]Huseyin Atakan Varol, Subramani Mani, Donald L. Compton, Lynn S. Fuchs, Douglas Fuchs:
Early Prediction of Reading Disability using Machine Learning. AMIA 2009 - 2007
- [c15]Subramani Mani, Constantin F. Aliferis:
A Causal Modeling Framework for Generating Clinical Practice Guidelines from Data. AIME 2007: 446-450 - [c14]Subramani Mani, Constantin F. Aliferis, Shanthi Krishnaswami, Theodore Kotchen:
Learning Causal and Predictive Clinical Practice Guidelines from Data. MedInfo 2007: 850-854 - 2006
- [c13]Subramani Mani, Gregory F. Cooper, Peter Spirtes:
A Theoretical Study of Y Structures for Causal Discovery. UAI 2006 - 2005
- [j2]Subramani Mani, Marco Valtorta, Suzanne McDermott:
Building Bayesian Network Models in Medicine: The MENTOR Experience. Appl. Intell. 22(2): 93-108 (2005) - 2004
- [c12]Subramani Mani, Gregory F. Cooper:
Causal Discovery Using A Bayesian Local Causal Discovery Algorithm. MedInfo 2004: 731-735 - 2001
- [c11]Subramani Mani, Gregory F. Cooper:
A Simulation Study of Three Related Causal Data Mining Algorithms. AISTATS 2001: 184-191 - 2000
- [c10]Subramani Mani, Gregory F. Cooper:
Causal discovery from medical textual data. AMIA 2000
1990 – 1999
- 1999
- [j1]Subramani Mani, William Rodman Shankle, Malcolm B. Dick, Michael J. Pazzani:
Two-Stage Machine Learning model for guideline development. Artif. Intell. Medicine 16(1): 51-71 (1999) - [c9]Subramani Mani, Gregory F. Cooper:
Causal Discovery from Population-Based Infant Birth and Death Records. AAAI/IAAI 1999: 973 - [c8]Subramani Mani, Malcolm B. Dick, Michael J. Pazzani, Evelyn L. Teng, Daniel Kempler, I. Maribell Taussig:
Refinement of Neuro-psychological Tests for Dementia Screening in a Cross Cultural Population Using Machine Learning. AIMDM 1999: 326-335 - [c7]Subramani Mani, Gregory F. Cooper:
A study in causal discovery from population-based infant birth and death records. AMIA 1999 - 1998
- [c6]Subramani Mani, Michael J. Pazzani:
Guideline generation from data by induction of decision tables using a Bayesian network framework. AMIA 1998 - [c5]William Rodman Shankle, Subramani Mani, Malcolm B. Dick, Michael J. Pazzani:
Simple Models for Estimating Dementia Severity Using Machine Learning. MedInfo 1998: 472-476 - 1997
- [c4]William Rodman Shankle, Subramani Mani, Michael J. Pazzani, Padhraic Smyth:
Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods. AIME 1997: 73-85 - [c3]Subramani Mani, Michael J. Pazzani, John West:
Knowledge Discovery from a Breast Cancer Database. AIME 1997: 130-133 - [c2]Subramani Mani, William Rodman Shankle, Michael J. Pazzani, Padhraic Smyth, Malcolm B. Dick:
Differential Diagnosis of Dementia: A Knowledge Discovery and Data Mining (KDD) Approach. AMIA 1997 - [c1]Michael J. Pazzani, Subramani Mani, William Rodman Shankle:
Beyond Concise and Colorful: Learning Intelligible Rules. KDD 1997: 235-238
Coauthor Index
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