Subramani Mani

37 papers A* 1A 2B 3Misc 9Journal 15Unranked 7

Year	Rank	Type	Title / Venue / Authors
2017	J	`jnl`	Formalizing drug indications on the road to therapeutic intent. J. Am. Medical Informatics Assoc. 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
2017	J	`jnl`	Pharos: Collating protein information to shed light on the druggable genome. Nucleic Acids Res. 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
2017	J	`jnl`	Protein biomarker druggability profiling. J. Biomed. Informatics Subramani Mani, Daniel Cannon, Robin Ohls, Tudor I. Oprea, Stephen L. Mathias, Karri Ballard, Oleg Ursu, Cristian Bologa
2017	J	`jnl`	TIN-X: target importance and novelty explorer. Bioinform. 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
2016	Misc	`conf`	Protein Biomarker Discovery and Ranking for Early Detection of Necrotizing Enterocolitis in Neonates. AMIA Subramani Mani, Daniel Cannon, Karri Ballard, Robin Ohls
2015	Misc	`conf`	Protein Drug Target Prioritization for Illumination. AMIA Subramani Mani, Daniel Cannon, Tudor I. Oprea, Stephen L. Mathias, Oleg Ursu, Cristian Bologa
2014	Misc	`conf`	Genomic dark matter, druggability and misunderstood targets. AMIA Subramani Mani, Joshua Swamidass, Noel Southall, Tudor I. Oprea
2014	J	`jnl`	Medical decision support using machine learning for early detection of late-onset neonatal sepsis. J. Am. Medical Informatics Assoc. 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
2013	J	`jnl`	Research and applications: Machine learning for predicting the response of breast cancer to neoadjuvant chemotherapy. J. Am. Medical Informatics Assoc. 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
2012	J	`jnl`	A theoretical study of Y structures for causal discovery. CoRR Subramani Mani, Peter Spirtes, Gregory F. Cooper
2012	J	`jnl`	Applying active learning to assertion classification of concepts in clinical text. J. Biomed. Informatics Yukun Chen, Subramani Mani, Hua Xu
2012	Misc	`conf`	Type 2 Diabetes Risk Forecasting from EMR Data using Machine Learning. AMIA Subramani Mani, Yukun Chen, Tom Elasy, Warren Clayton, Joshua C. Denny
2011	J	`jnl`	A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries. J. Am. Medical Informatics Assoc. Min Jiang, Yukun Chen, Mei Liu, S. Trent Rosenbloom, Subramani Mani, Joshua C. Denny, Hua Xu
2011	—	`conf`	Active Learning for Unbalanced Data in the Challenge with Multiple Models and Biasing. Active Learning and Experimental Design @ AISTATS Yukun Chen, Subramani Mani
2010	—	`conf`	Bayesian Algorithms for Causal Data Mining. NIPS Causality: Objectives and Assessment Subramani Mani, Constantin F. Aliferis, Alexander R. Statnikov
2010	J	`jnl`	Identifying potential drugs that induce QT prolongation using electronic medical records. BMC Bioinform. Mei Liu, Joshua C. Denny, Subramani Mani, Yukun Chen, Yong Hu, Hua Xu
2010	J	`jnl`	Letter: Note on Friedman's 'fundamental theorem of biomedical informatics'. J. Am. Medical Informatics Assoc. Subramani Mani
2010	J	`jnl`	Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation. J. Mach. Learn. Res. Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos
2010	J	`jnl`	Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions. J. Mach. Learn. Res. Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos
2009	Misc	`conf`	Early Prediction of Reading Disability using Machine Learning. AMIA Huseyin Atakan Varol, Subramani Mani, Donald L. Compton, Lynn S. Fuchs, Douglas Fuchs
2007	B	`conf`	A Causal Modeling Framework for Generating Clinical Practice Guidelines from Data. AIME Subramani Mani, Constantin F. Aliferis
2007	—	`conf`	Learning Causal and Predictive Clinical Practice Guidelines from Data. MedInfo Subramani Mani, Constantin F. Aliferis, Shanthi Krishnaswami, Theodore Kotchen
2006	A	`conf`	A Theoretical Study of Y Structures for Causal Discovery. UAI Subramani Mani, Gregory F. Cooper, Peter Spirtes
2005	J	`jnl`	Building Bayesian Network Models in Medicine: The MENTOR Experience. Appl. Intell. Subramani Mani, Marco Valtorta, Suzanne McDermott
2004	—	`conf`	Causal Discovery Using A Bayesian Local Causal Discovery Algorithm. MedInfo Subramani Mani, Gregory F. Cooper
2001	A	`conf`	A Simulation Study of Three Related Causal Data Mining Algorithms. AISTATS Subramani Mani, Gregory F. Cooper
2000	Misc	`conf`	Causal discovery from medical textual data. AMIA Subramani Mani, Gregory F. Cooper
1999	Misc	`conf`	A study in causal discovery from population-based infant birth and death records. AMIA Subramani Mani, Gregory F. Cooper
1999	—	`conf`	Causal Discovery from Population-Based Infant Birth and Death Records. AAAI/IAAI Subramani Mani, Gregory F. Cooper
1999	—	`conf`	Refinement of Neuro-psychological Tests for Dementia Screening in a Cross Cultural Population Using Machine Learning. AIMDM Subramani Mani, Malcolm B. Dick, Michael J. Pazzani, Evelyn L. Teng, Daniel Kempler, I. Maribell Taussig
1999	J	`jnl`	Two-Stage Machine Learning model for guideline development. Artif. Intell. Medicine Subramani Mani, William Rodman Shankle, Malcolm B. Dick, Michael J. Pazzani
1998	Misc	`conf`	Guideline generation from data by induction of decision tables using a Bayesian network framework. AMIA Subramani Mani, Michael J. Pazzani
1998	—	`conf`	Simple Models for Estimating Dementia Severity Using Machine Learning. MedInfo William Rodman Shankle, Subramani Mani, Malcolm B. Dick, Michael J. Pazzani
1997	A*	`conf`	Beyond Concise and Colorful: Learning Intelligible Rules. KDD Michael J. Pazzani, Subramani Mani, William Rodman Shankle
1997	B	`conf`	Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods. AIME William Rodman Shankle, Subramani Mani, Michael J. Pazzani, Padhraic Smyth
1997	Misc	`conf`	Differential Diagnosis of Dementia: A Knowledge Discovery and Data Mining (KDD) Approach. AMIA Subramani Mani, William Rodman Shankle, Michael J. Pazzani, Padhraic Smyth, Malcolm B. Dick
1997	B	`conf`	Knowledge Discovery from a Breast Cancer Database. AIME Subramani Mani, Michael J. Pazzani, John West