Preeclampsia Predictor with Machine Learning: A Comprehensive and Bias-Free Machine Learning Pipeline
Yun C. Lin, Daniel Mallia, Andrea O. Clark-Sevilla, Adam Catto, Alisa Leshchenko, David M. Haas, Ronald Wapner, Itsik Pe’er, Anita Raja, Ansaf Salleb-Aouissi
medRxiv 2022
[paper]
Interpretable prediction of necrotizing enterocolitis from machine learning analysis of premature infant stool microbiota
Lin, Yun Chao, Ansaf Salleb-Aouissi, and Thomas A. Hooven
BMC Bioinformatics 2022
[paper]
Genetic Polymorphisms Associated with Adverse Pregnancy Outcomes in Nulliparas
Rafael F.Guerrero, Raiyan R. Khan, Ronald J.Wapner, Matthew W. Hahn, Anita Raja, Ansaf Salleb-Aouissi, William A. Grobman, Hyagriv Simhan, Robert Silver, Judith H. Chung, Uma M. Reddy, Predrag Radivojac, Itsik Pe’er, David M. Haas.
Under review AJOG 2022
[paper]
Data Preparation of the nuMoM2b Dataset
Anton Goretsky, Anastasia Dmitrienko, Irene Tang, Nicolae Lari, Owen Kunhardt, Raiyan Rashid Khan,Cassandra Marcussen, Adam Catto, Daniel Mallia, Alisa Leshchenko, Adam (Yun Chao) Lin, Anita Raja, Ansaf Salleb-Aouissi, Itsik Pe’err, Ronald Wapner, Cynthia Gyamfi-Bannerman
medRxiv 2021
[paper]
Automated Symbolic Law Discovery: A Computer Vision Approach
Xing, H., Salleb-Aouissi, A., & Verma, N
Proceedings of the AAAI Conference on Artificial Intelligence 2021
[paper]
Multiple instance learning for predicting necrotizing enterocolitis in premature infants using microbiome data
Hooven, Thomas, Yun Chao Lin, and Ansaf Salleb-Aouissi
Proceedings of the ACM Conference on Health, Inference, and Learning 2020
[paper]
A Weighted Solution to SVM Actionability and Interpretability
SM Denton, A Salleb-Aouissi
arXiv preprint arXiv:2012.03372, 2020
[paper]
Using Privileged Information to Improve Prediction in Health Data: A Case Study
Jongoh Jeong, Do Hyung Kwon, Min Joon So, Anita Raja, Shivani Ghatge, Nicolae Lari, Ansaf Salleb-Aouissi
Workshop on Information Theory and Machine Learning 2019
[paper]
Toward a Robust Crowd-Labeling Framework Using Expert Evaluation and Pairwise Comparison
FK Khattak, A Salleb-Aouissi
arXiv preprint arXiv:1607.02174, 2016
[paper]
Using Kernel Methods and Model Selection for Prediction of Preterm Birth
Ilia Vovsha, Ansaf Salleb-Aouissi, Anita Raja, Thomas Koch, Alex Rybchuk, Axinia Radeva, Ashwath Rajan, Yiwen Huang, Hatim Diab, Ashish Tomar, Ronald Wapner
Proceeding of Machine Learning Research 2016
[paper]
Diving into a Large Corpus of Pediatric Notes
The Office of the Executive Vice President for Research, Research Social Hour
[paper]
Application of Sentiment and Topic Analysis to Teacher Evaluation Policy in The US
A Moretti, K McKnight, A Salleb-Aouissi
Educational Data Mining Conference (EDM) 2015
[paper]
Learning Characteristic Rules in Geographic Information Systems
Ansaf Salleb-Aouissi, Christel Vrain, Daniel Cassard
Rule Technologies: Foundations, Tools, and Applications, 9th International Symposium 2015
paper]
Predicting Preterm Birth is Not Elusive: Machine Learning Paves The Way to Individual Wellness
Ilia Vovsha, Ashwath Rajan, Ansaf Salleb-Aouissi, Anita Raja , Axinia Radeva, Hatim Diab, Ashish Tomar and Ronald Wapner
Association for the Advancement of Artificial Intelligence (AAAI) 2014
[paper]
QuantMiner for Mining Auantitative Association Rules
Ansaf Salleb-Aouissi, Christel Vrain, Cyril Nortet, Xiangrong Kong, Vivek Rathod, and Daniel Cassard
J. Mach. Learn. Res. 2013
[paper]
Building actions from Classification Rules
Trépos, R., Salleb-Aouissi, A., Cordier, MO. et al.
Knowl Inf Syst 2013
[paper]
Robust Crowd Labeling Using Little Expertise
Khattak, F.K., Salleb-Aouissi, A.
Discovery Science 2013
[paper]
Improving Crowd Labeling through Expert Evaluation
Khattak, Faiza Khan and Ansaf Salleb-Aouissi
AAAI Spring Symposium: Wisdom of the Crowd 2012
[paper]
Multiplicity and word sense: evaluating and learning from multiply labeled word sense annotations
Passonneau, R.J., Bhardwaj, V., Salleb-Aouissi, A. et al.
Lang Resources & Evaluation 2012
[paper]
Machine Learning for the New York City Power Grid
C. Rudin et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence 2012
[paper]
Quality Control of Crowd Labeling through Expert Evaluation
Khattak, Faiza & Salleb, Ansaf
2011
[paper]
Diving into a Large Corpus of Pediatric Notes
Ansaf Salleb-Aouissi, Axinia Radeva, Rebecca Passonneau, Boyi Xie, Faiza Khan Khattak, Ashish Tomar, David Waltz, Mary McCord, Harriet McGurk, and Noemie Elhadad
ICML 2011 Workshop 2011
[paper] [poster]
Prediction with Association Rules
Cynthia Rudin, Benjamin Letham, Ansaf Salleb-Aouissi, Eugene Kogan, David Madigan. Sequential Event
Proceedings of the 24th Annual Conference on Learning Theory 2011
[paper]
Word Sense Annotation of Polysemous Words by Multiple Annotators
Rebecca J. Passonneau, Ansaf Salleb-Aoussi, Vikas Bhardwaj, and Nancy Ide
Seventh International Conference on Language Resources and Evaluation 2010
[paper]
A Framework for Analysis of Multiple Annotators’ Labeling Behavior
Vikas Bhardwaj, Rebecca Passonneau, Ansaf Salleb-Aouissi, and Nancy Ide
Fourth Linguistic Annotation Workshop 2010
[paper]
A Perspective on Understanding Infantile Colic
Ansaf Salleb-Aouissi, Axinia Radeva, Rebecca Passonneau, Ashish Tomar, David Waltz, Mary McCord, Harriet McGurk, Noemie Elhadad
NIPS Workshop 2010
[paper]
Ranking Electrical Feeders of the New York Power Grid
P. Gross, A. Salleb-Aouissi, H. Dutta and A. Boulanger
International Conference on Machine Learning and Applications 2009
[paper]
Estimating the Time Between Failures of Electrical Feeders in the New York Power Grid
Dutta, Haimonti & Waltz, David & Moschitti, Alessandro & Pighin, Daniele & Gross, Philip & Monteleoni, Claire & Salleb, Ansaf & Boulanger, Albert & Pooleery, Manoj & Anderson, Roger
Next Generation Data Mining Summit 2009
[paper]
[2009]
Alive on Back-feed Culprit Identification via Machine Learning
B. Huang, A. Salleb-Aouissi and P. Gross
International Conference on Machine Learning and Applications 2009
[paper]
Discovering Characterization Rules from Rankings
A. Salleb-Aouissi, B. Huang and D. Waltz
International Conference on Machine Learning and Applications 2009
[paper]
QuantMiner: A Genetic Algorithm for Mining Quantitative Association Rules
Salleb, Ansaf & Vrain, C. & Nortet, Cyril
IJCAI International Joint Conference on Artificial Intelligence 2007
[paper]
On the Discovery of Exception Rules: A Survey
Duval, B., Salleb, A., Vrain, C.
Studies in Computational Intelligence 2007
[paper]
A Distance-Based Approach for Action Recommendation
Trepos, R., Salleb, A., Cordier, MO., Masson, V., Gascuel, C.
Machine Learning: ECML 2005
[paper]
Mining Quantitative Association Rules in a Atherosclerosis Dataset.
Salleb, Ansaf & Turmeaux, Teddy & Vrain, Christel & Nortet, Cyril
2004
[paper]
Learning Characteristic Rules Relying on Quantified Paths.
Turmeaux, T., Salleb, A., Vrain, C., Cassard, D.
Knowledge Discovery in Databases: PKDD 2003
[paper]
Mining maximal frequent itemsets by a boolean based approach
Ansaf Salleb, Zahir Maazouzi, and Christel Vrain
15th European Conference on Artificial Intelligence 2002
[paper]
Quantitative assessments of a continent-scale metallogenic GIS by data-driven and knowledge-driven approaches to construct decision-aid documents
Lips, A. L. W., et al.
GIS in Geology Int. Conference 2002
An Application of Association Rules Discovery to Geographic Information Systems.
Salleb, A., Vrain, C.
Principles of Data Mining and Knowledge Discovery 2000
[paper]