Subramani Mani

Publication Activity (10 Years)

Years Active: 1997-2017
Publications (10 Years): 5

Top Topics

Machine Learning

Early Detection

Conceptual Retrieval

Top Venues

J. Am. Medical Informatics Assoc.

J. Biomed. Informatics

Publications

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) (2017)
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 (2017)
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) (2017)
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) (2017)
Subramani Mani, Daniel Cannon, Karri Ballard, Robin Ohls
Protein Biomarker Discovery and Ranking for Early Detection of Necrotizing Enterocolitis in Neonates. AMIA (2016)
Subramani Mani, Daniel Cannon, Tudor I. Oprea, Stephen L. Mathias, Oleg Ursu, Cristian Bologa
Protein Drug Target Prioritization for Illumination. AMIA (2015)
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) (2014)
Subramani Mani, Joshua Swamidass, Noel Southall, Tudor I. Oprea
Genomic dark matter, druggability and misunderstood targets. AMIA (2014)
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) (2013)
Subramani Mani, Peter Spirtes, Gregory F. Cooper
A theoretical study of Y structures for causal discovery. CoRR (2012)
Subramani Mani, Yukun Chen, Tom Elasy, Warren Clayton, Joshua C. Denny
Type 2 Diabetes Risk Forecasting from EMR Data using Machine Learning. AMIA (2012)
Yukun Chen, Subramani Mani, Hua Xu
Applying active learning to assertion classification of concepts in clinical text. J. Biomed. Informatics 45 (2) (2012)
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) (2011)
Yukun Chen, Subramani Mani
Active Learning for Unbalanced Data in the Challenge with Multiple Models and Biasing. Active Learning and Experimental Design @ AISTATS (2011)
Subramani Mani
Letter: Note on Friedman's 'fundamental theorem of biomedical informatics'. J. Am. Medical Informatics Assoc. 17 (5) (2010)
Subramani Mani, Constantin F. Aliferis, Alexander R. Statnikov
Bayesian Algorithms for Causal Data Mining. NIPS Causality: Objectives and Assessment (2010)
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) (2010)
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 (2010)
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 (2010)
Huseyin Atakan Varol, Subramani Mani, Donald L. Compton, Lynn S. Fuchs, Douglas Fuchs
Early Prediction of Reading Disability using Machine Learning. AMIA (2009)
Subramani Mani, Constantin F. Aliferis
A Causal Modeling Framework for Generating Clinical Practice Guidelines from Data. AIME (2007)
Subramani Mani, Constantin F. Aliferis, Shanthi Krishnaswami, Theodore Kotchen
Learning Causal and Predictive Clinical Practice Guidelines from Data. MedInfo (2007)
Subramani Mani, Gregory F. Cooper, Peter Spirtes
A Theoretical Study of Y Structures for Causal Discovery. UAI (2006)
Subramani Mani, Marco Valtorta, Suzanne McDermott
Building Bayesian Network Models in Medicine: The MENTOR Experience. Appl. Intell. 22 (2) (2005)
Subramani Mani, Gregory F. Cooper
Causal Discovery Using A Bayesian Local Causal Discovery Algorithm. MedInfo (2004)
Subramani Mani, Gregory F. Cooper
A Simulation Study of Three Related Causal Data Mining Algorithms. AISTATS (2001)
Subramani Mani, Gregory F. Cooper
Causal discovery from medical textual data. AMIA (2000)
Subramani Mani, Gregory F. Cooper
Causal Discovery from Population-Based Infant Birth and Death Records. AAAI/IAAI (1999)
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)
Subramani Mani, Gregory F. Cooper
A study in causal discovery from population-based infant birth and death records. AMIA (1999)
Subramani Mani, William Rodman Shankle, Malcolm B. Dick, Michael J. Pazzani
Two-Stage Machine Learning model for guideline development. Artif. Intell. Medicine 16 (1) (1999)
Subramani Mani, Michael J. Pazzani
Guideline generation from data by induction of decision tables using a Bayesian network framework. AMIA (1998)
William Rodman Shankle, Subramani Mani, Malcolm B. Dick, Michael J. Pazzani
Simple Models for Estimating Dementia Severity Using Machine Learning. MedInfo (1998)
Subramani Mani, Michael J. Pazzani, John West
Knowledge Discovery from a Breast Cancer Database. AIME (1997)
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)
Michael J. Pazzani, Subramani Mani, William Rodman Shankle
Beyond Concise and Colorful: Learning Intelligible Rules. KDD (1997)
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)