Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL
Machine Learning - Special issue on applications of machine learning and the knowledge discovery process
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
The Life of a Logic Programming System
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
Information Extraction for Clinical Data Mining: A Mammography Case Study
ICDMW '09 Proceedings of the 2009 IEEE International Conference on Data Mining Workshops
An inductive logic programming approach to validate Hexose binding biochemical knowledge
ILP'09 Proceedings of the 19th international conference on Inductive logic programming
A probabilistic interpretation of precision, recall and F-score, with implication for evaluation
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Prediction of Breast Cancer Using Artificial Neural Networks
Journal of Medical Systems
Relational differential prediction
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
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Breast cancer is the most common type of cancer among women. Current clinical breast cancer diagnosis involves a biopsy, which is a costly, invasive and potentially painful procedure. Some researchers proposed models, based on mammography features and personal information, that help identify pre-biopsy invasive breast carcinoma and ductal carcinoma in situ (DCIS). Recently, a differential discriminating ability between invasive and DCIS has been linked to age. Based on this finding, we use an age-stratified mammography and biopsy relational dataset and apply Inductive Logic Programming (ILP) techniques to learn age-specific logical rules that classify invasive and DCIS occurrences. We then use statistical modeling to retrieve rules that have a significantly different performance across age-stratas. These final rules reveal a number of interesting results. Although a palpable lump is more commonly associated with younger patients, it turns out to be a better predictor of invasive cancer in older women. A recurrence has a higher probability to be invasive in older and middle-aged women. A previously unreported rule revealed by our technique is that recurrence is more likely a DCIS predictor in younger women. This younger DCIS predicting rule effectively links the current diagnostic mammogram to older studies, and provides opposite predictions across the age divide. The resulting rules are age-specific, can help patients and their physicians make more informed decisions about managing their breast health, and constitute a personalized predictive model.