Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Methodological Review: What can natural language processing do for clinical decision support?
Journal of Biomedical Informatics
Cancer stage prediction based on patient online discourse
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Tracking sentiment in mail: how genders differ on emotional axes
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
Proactive screening for depression through metaphorical and automatic text analysis
Artificial Intelligence in Medicine
Portable features for classifying emotional text
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Detecting distressed and non-distressed affect states in short forum texts
LSM '12 Proceedings of the Second Workshop on Language in Social Media
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We hypothesize that machine-learning algorithms (MLA) can classify completer and simulated suicide notes as well as mental health professionals (MHP). Five MHPs classified 66 simulated or completer notes; MLAs were used for the same task. Results: MHPs were accurate 71% of the time; using the sequential minimization optimization algorithm (SMO) MLAs were accurate 78% of the time. There was no significant difference between the MLA and MPH classifiers. This is an important first step in developing an evidence based suicide predictor for emergency department use.