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A large number of taxonomies are used to rate the quality of an individual study and the strength of a recommendation based on a body of evidence. We have developed a new grading scale that will be used by several family medicine and primary care journals (required or optional), with the goal of allowing readers to learn one taxonomy that will apply to many(More)
OBJECTIVE To identify the most frequent obstacles preventing physicians from answering their patient-care questions and the most requested improvements to clinical information resources. DESIGN Qualitative analysis of questions asked by 48 randomly selected generalist physicians during ambulatory care. MEASUREMENTS Frequency of reported obstacles to(More)
This project develops a computational method to improve searches of the medical literature by selecting the studies that report reliable evidence of patient-oriented outcomes. These outcomes include morbidity, mortality, symptom severity, and quality of life. Four machine learning methods, Support Vector Machines, na¨ıve bayes, na¨ıve bayes multinomial and(More)
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