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A distributed ensemble approach for mining healthcare data under privacy constraints

A distributed ensemble approach for mining healthcare data under privacy constraints

Starting at: Rs.5,500.00

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 A distributed ensemble approach for mining healthcare data under privacy constraints

Electronic health records (EHRs) have been widely adapted at many healthcare facilities in an attempt to improve the quality of patient care and increase the productivity and efficiency of healthcare delivery. These EHRs can accurately diagnose diseases if utilized ap-propriately. While the EHRs can potentially resolve many of the existing problems associated with disease diagnosis, one of the main obstacles in effectively using them is the patient pri-vacy and sensitivity of the medical information available in the EHR. Due to these concerns, even if the EHRs are available for storage and retrieval purposes, sharing of the patient records between different healthcare facilities has become a major concern and has hampered some of the effective advantages of using EHRs. Due to this lack of data sharing, most of the facilities aim at building clinical decision support systems using limited amount of patient data from their own EHR systems to provide important diagnosis related decisions. It becomes quite in-feasible for a newly established healthcare facility to build a robust decision making system due to the lack of sufficient patient records. However, to make effective decisions from clinical data, it is indispensable to have large amounts of data to train the decision models. In this re-gard, there are conflicting objectives of preserving patient privacy and having sufficient data for modeling and decision making


 


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  • Model: PROJ7592
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

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This product was added to our catalog on Monday 31 July, 2017.

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