Cross-Topic Learning for Work Prioritization in Systematic Review Creation and Update
Open Access
- 1 September 2009
- journal article
- research article
- Published by Oxford University Press (OUP) in Journal of the American Medical Informatics Association
- Vol. 16 (5) , 690-704
- https://doi.org/10.1197/jamia.m3162
Abstract
Objective: Machine learning systems can be an aid to experts performing systematic reviews (SRs) by automatically ranking journal articles for work-pKeywords
This publication has 39 references indexed in Scilit:
- Towards Automatic Recognition of Scientifically Rigorous Clinical Research EvidenceJournal of the American Medical Informatics Association, 2009
- Identifying Patient Smoking Status from Medical Discharge RecordsJournal of the American Medical Informatics Association, 2008
- A method for probabilistic mapping between protein structure and function taxonomies through cross trainingBMC Structural Biology, 2008
- Jottings...BMJ Evidence-Based Medicine, 2006
- A Comparison of Citation Metrics to Machine Learning Filters for the Identification of High Quality MEDLINE DocumentsJournal of the American Medical Informatics Association, 2006
- Knowledge for knowledge translation: The role of the Cochrane CollaborationJournal of Continuing Education in the Health Professions, 2006
- Incorporating Information About Cost-Effectiveness Into Evidence-Based Decision-MakingMedical Care, 2005
- Text Categorization Models for High-Quality Article Retrieval in Internal MedicineJournal of the American Medical Informatics Association, 2004
- The use of the area under the ROC curve in the evaluation of machine learning algorithmsPattern Recognition, 1997
- EditorialMedical Decision Making, 1993