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Mendeley readers
Title |
Multivariate modeling to identify patterns in clinical data: the example of chest pain
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Published in |
BMC Medical Research Methodology, November 2011
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DOI | 10.1186/1471-2288-11-155 |
Pubmed ID | |
Authors |
Oliver Hirsch, Stefan Bösner, Eyke Hüllermeier, Robin Senge, Krzysztof Dembczynski, Norbert Donner-Banzhoff |
Abstract |
In chest pain, physicians are confronted with numerous interrelationships between symptoms and with evidence for or against classifying a patient into different diagnostic categories. The aim of our study was to find natural groups of patients on the basis of risk factors, history and clinical examination data which should then be validated with patients' final diagnoses. |
Mendeley readers
The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 1 | 2% |
Argentina | 1 | 2% |
Unknown | 44 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 8 | 17% |
Student > Master | 7 | 15% |
Student > Ph. D. Student | 6 | 13% |
Student > Bachelor | 5 | 11% |
Student > Postgraduate | 3 | 7% |
Other | 5 | 11% |
Unknown | 12 | 26% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 10 | 22% |
Computer Science | 5 | 11% |
Business, Management and Accounting | 3 | 7% |
Mathematics | 3 | 7% |
Agricultural and Biological Sciences | 2 | 4% |
Other | 10 | 22% |
Unknown | 13 | 28% |