Constructive Induction in Knowledge-Based Neural Networks. - Geoffrey G. Towell; Mark W. Craven; Jude W. Shavlik (ML, 1991)

Visualizing Learning and Computation in Artificial Neural Networks. - Mark W. Craven; Jude W. Shavlik (Int. J. Artif. Intell. Tools, 1992)

Learning Symbolic Rules Using Artificial Neural Networks. - Mark W. Craven; Jude W. Shavlik (ICML, 1993)

Learning to Represent Codons: A Challenge Problem for Constructive Induction. - Mark W. Craven; Jude W. Shavlik (IJCAI, 1993)

Using Sampling and Queries to Extract Rules from Trained Neural Networks. - Mark W. Craven; Jude W. Shavlik (ICML, 1994)

Machine Learning Approaches to Gene Recognition. - Mark W. Craven; Jude W. Shavlik (IEEE Expert, 1994)

Extracting Tree-Structured Representations of Trained Networks. - Mark W. Craven; Jude W. Shavlik (NIPS, 1995)

Using neural networks to automatically refine expert system knowledge bases: experiments in the NYNEX MAX domain. - David W. Opitz; Mark W. Craven; Jude W. Shavlik (ICNN, 1997)

Using neural networks for data mining. - Mark W. Craven; Jude W. Shavlik (Future Gener. Comput. Syst., 1997)

Understanding Time-Series Networks: A Case Study in Rule Extraction. - Mark W. Craven; Jude W. Shavlik (Int. J. Neural Syst., 1997)

Using Multiple Levels of Learning and Diverse Evidence to Uncover Coordinately Controlled Genes. - Mark W. Craven; David Page; Jude W. Shavlik; Joseph Bockhorst; Jeremy D. Glasner (ICML, 2000)

A Probabilistic Learning Approach to Whole-Genome Operon Prediction. - Mark W. Craven; David Page; Jude W. Shavlik; Joseph Bockhorst; Jeremy D. Glasner (ISMB, 2000)

A Bayesian Network Approach to Operon Prediction. - Joseph Bockhorst; Mark W. Craven; David Page; Jude W. Shavlik; Jeremy D. Glasner (Bioinform., 2003)

Learning to Predict Post-Hospitalization VTE Risk from EHR Data. - Emily Kawaler; Alexander G. Cobian; Peggy L. Peissig; Deanna S. Cross; Steven Yale; Mark W. Craven (AMIA, 2012)

Big Data in Healthcare: Opportunities and Challenges. - Mark W. Craven; C. David Page (Big Data, 2015)

Modeling the Temporal Evolution of Postoperative Complications. - Shara I. Feld; Alexander G. Cobian; Sarah E. Tevis; Gregory D. Kennedy; Mark W. Craven (AMIA, 2016)

Computational Phenotyping on Diverse Data Sources. - Jimeng Sun 001; Bradley A. Malin; Abel N. Kho; Mark W. Craven; Joydeep Ghosh (AMIA, 2017)

Breast Cancer Risk Prediction Using Electronic Health Records. - Yirong Wu; Elizabeth S. Burnside; Jennifer Cox; Jun Fan; Ming Yuan 001; Jie Yin; Peggy L. Peissig; Alexander G. Cobian; David Page; Mark W. Craven (ICHI, 2017)