Knowledge Discovery from a Breast Cancer Database. - Subramani Mani; Michael J. Pazzani; John West (AIME, 1997)

Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods. - William Rodman Shankle; Subramani Mani; Michael J. Pazzani; Padhraic Smyth (AIME, 1997)

Differential Diagnosis of Dementia: A Knowledge Discovery and Data Mining (KDD) Approach. - Subramani Mani; William Rodman Shankle; Michael J. Pazzani; Padhraic Smyth; Malcolm B. Dick (AMIA, 1997)

Beyond Concise and Colorful: Learning Intelligible Rules. - Michael J. Pazzani; Subramani Mani; William Rodman Shankle (KDD, 1997)

Guideline generation from data by induction of decision tables using a Bayesian network framework. - Subramani Mani; Michael J. Pazzani (AMIA, 1998)

Simple Models for Estimating Dementia Severity Using Machine Learning. - William Rodman Shankle; Subramani Mani; Malcolm B. Dick; Michael J. Pazzani (MedInfo, 1998)

Causal Discovery from Population-Based Infant Birth and Death Records. - Subramani Mani; Gregory F. Cooper (AAAI/IAAI, 1999)

Refinement of Neuro-psychological Tests for Dementia Screening in a Cross Cultural Population Using Machine Learning. - Subramani Mani; Malcolm B. Dick; Michael J. Pazzani; Evelyn L. Teng; Daniel Kempler; I. Maribell Taussig (AIMDM, 1999)

A study in causal discovery from population-based infant birth and death records. - Subramani Mani; Gregory F. Cooper (AMIA, 1999)

Two-Stage Machine Learning model for guideline development. - Subramani Mani; William Rodman Shankle; Malcolm B. Dick; Michael J. Pazzani (Artif. Intell. Medicine, 1999)

Causal discovery from medical textual data. - Subramani Mani; Gregory F. Cooper (AMIA, 2000)

A Simulation Study of Three Related Causal Data Mining Algorithms. - Subramani Mani; Gregory F. Cooper (AISTATS, 2001)

Causal Discovery Using A Bayesian Local Causal Discovery Algorithm. - Subramani Mani; Gregory F. Cooper (MedInfo, 2004)

Building Bayesian Network Models in Medicine: The MENTOR Experience. - Subramani Mani; Marco Valtorta; Suzanne McDermott (Appl. Intell., 2005)

A Theoretical Study of Y Structures for Causal Discovery. - Subramani Mani; Gregory F. Cooper; Peter Spirtes (UAI, 2006)

A Causal Modeling Framework for Generating Clinical Practice Guidelines from Data. - Subramani Mani; Constantin F. Aliferis (AIME, 2007)

Learning Causal and Predictive Clinical Practice Guidelines from Data. - Subramani Mani; Constantin F. Aliferis; Shanthi Krishnaswami; Theodore Kotchen (MedInfo, 2007)

Early Prediction of Reading Disability using Machine Learning. - Huseyin Atakan Varol; Subramani Mani; Donald L. Compton; Lynn S. Fuchs; Douglas Fuchs (AMIA, 2009)

Identifying potential drugs that induce QT prolongation using electronic medical records. - Mei Liu; Joshua C. Denny; Subramani Mani; Yukun Chen 001; Yong Hu 002; Hua Xu 001 (BMC Bioinform., 2010)

Letter: Note on Friedman's 'fundamental theorem of biomedical informatics'. - Subramani Mani (J. Am. Medical Informatics Assoc., 2010)

Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation. - Constantin F. Aliferis; Alexander R. Statnikov; Ioannis Tsamardinos; Subramani Mani; Xenofon D. Koutsoukos (J. Mach. Learn. Res., 2010)

Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions. - Constantin F. Aliferis; Alexander R. Statnikov; Ioannis Tsamardinos; Subramani Mani; Xenofon D. Koutsoukos (J. Mach. Learn. Res., 2010)

Bayesian Algorithms for Causal Data Mining. - Subramani Mani; Constantin F. Aliferis; Alexander R. Statnikov (NIPS Causality: Objectives and Assessment, 2010)

A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries. - Min Jiang 007; Yukun Chen 001; Mei Liu; S. Trent Rosenbloom; Subramani Mani; Joshua C. Denny; Hua Xu 001 (J. Am. Medical Informatics Assoc., 2011)

Active Learning for Unbalanced Data in the Challenge with Multiple Models and Biasing. - Yukun Chen 001; Subramani Mani (Active Learning and Experimental Design @ AISTATS, 2011)

Type 2 Diabetes Risk Forecasting from EMR Data using Machine Learning. - Subramani Mani; Yukun Chen 001; Tom Elasy; Warren Clayton; Joshua C. Denny (AMIA, 2012)

Applying active learning to assertion classification of concepts in clinical text. - Yukun Chen 001; Subramani Mani; Hua Xu 001 (J. Biomed. Informatics, 2012)

Research and applications: Machine learning for predicting the response of breast cancer to neoadjuvant chemotherapy. - Subramani Mani; Yukun Chen 001; Xia Li; Lori R. Arlinghaus; A. Bapsi Chakravarthy; Vandana G. Abramson; Sandeep R. Bhave; Mia A. Levy; Hua Xu 001; Thomas E. Yankeelov (J. Am. Medical Informatics Assoc., 2013)

Genomic dark matter, druggability and misunderstood targets. - Subramani Mani; Joshua Swamidass; Noel Southall; Tudor I. Oprea (AMIA, 2014)

Medical decision support using machine learning for early detection of late-onset neonatal sepsis. - Subramani Mani; Asli Ozdas; Constantin F. Aliferis; Huseyin Atakan Varol; Qingxia Chen; Randy J. Carnevale; Yukun Chen 001; Joann Romano-Keeler; Hui Nian; Jörn-Hendrik Weitkamp (J. Am. Medical Informatics Assoc., 2014)

Protein Drug Target Prioritization for Illumination. - Subramani Mani; Daniel Cannon; Tudor I. Oprea; Stephen L. Mathias; Oleg Ursu; Cristian Bologa (AMIA, 2015)

Protein Biomarker Discovery and Ranking for Early Detection of Necrotizing Enterocolitis in Neonates. - Subramani Mani; Daniel Cannon; Karri Ballard; Robin Ohls (AMIA, 2016)

TIN-X: target importance and novelty explorer. - 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 (Bioinform., 2017)

Formalizing drug indications on the road to therapeutic intent. - 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 (J. Am. Medical Informatics Assoc., 2017)

Protein biomarker druggability profiling. - Subramani Mani; Daniel Cannon; Robin Ohls; Tudor I. Oprea; Stephen L. Mathias; Karri Ballard; Oleg Ursu; Cristian Bologa (J. Biomed. Informatics, 2017)

Pharos: Collating protein information to shed light on the druggable genome. - 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; et al. (Nucleic Acids Res., 2017)