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Published, Version of Record (VoR)CC BY V4.0, Open
Journal article
BPLT+: A Bayesian-based personalized recommendation model for health care
BMC genomics, v 14(Suppl 4), pp S6-S6
01 Oct 2013
PMID: 24266984
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
In this paper, we propose an Advanced Bayesian-based Personalized Laboratory Tests recommendation (BPLT
+
) model. Given a patient, we estimate whether a new laboratory test should belong to a "taken" or "not-taken" class. We use the bayesian method to build a weighting function for a laboratory test and the given patient. A higher weight represents that the laboratory test has a higher probability of being "taken" by the patient and lower probability of being "not-taken" by the patient. For the sake of effectiveness and robustness, we further integrate several modified smoothing techniques into the model. In order to evaluate BPLT
+
model objectively, we propose a framework where the data set is randomly split into a training set, a validation input set and a validation label set. A training matrix is generated from the training data set. Then instead of accessing the training data set repeatedly, we utilize this training matrix to predict the laboratory test on the validation input set. Finally, the recommended ranking list is compared with the validation label set using our proposed metric
CorrectRate
M
. We conduct experiments on real medical data, and the experimental results show the effectiveness of the proposed BPLT
+
model.
Metrics
Details
- Title
- BPLT+: A Bayesian-based personalized recommendation model for health care
- Creators
- Jiashu Zhao - York UniversityJimmy Xiangji Huang - York UniversityXiaohua Hu - Drexel University
- Publication Details
- BMC genomics, v 14(Suppl 4), pp S6-S6
- Publisher
- BioMed Central
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000326801200006
- Scopus ID
- 2-s2.0-84899631807
- Other Identifier
- 991019167528704721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Biotechnology & Applied Microbiology
- Genetics & Heredity