Next Article in Journal
Design of All-Solid Dual-Concentric-Core Microstructure Fiber for Ultra-Broadband Dispersion Compensation
Previous Article in Journal
Research on Lifespan Prediction of Composite Insulators in a High Altitude Area Experimental Station
Open AccessArticle

iHealthcare: Predictive Model Analysis Concerning Big Data Applications for Interactive Healthcare Systems

Department of Computer Science and Engineering, East West University, Dhaka-1212, Bangladesh
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in ICIEV & ISCMHT 2017, IEEE, Himeji, Japan, 1–3 September 2017, doi:10.1109/ICIEV.2017.8338606.
Appl. Sci. 2019, 9(16), 3365; https://doi.org/10.3390/app9163365
Received: 23 May 2019 / Revised: 16 July 2019 / Accepted: 25 July 2019 / Published: 15 August 2019
Recently, the healthcare industry has caught the attention of researchers due to a need to develop a smart and interactive system for effective and efficient treatment facilities. The healthcare system consists of massive biological data (unstructured or semi-structured) which needs to be analyzed and processed for early disease detection. In this paper, we have designed a piece of healthcare technology which can deal with a patient’s past and present medical data including symptoms of a disease, emotional data, and genetic data. We have designed a probabilistic data acquisition scheme to analyze the medical data. This model contains a data warehouse with a two-way interaction between high-performance computing and cloud synchronization. Finally, we present a prediction scheme that is performed in the cloud server to predict disease in a patient. To complete this task, we used Random Forest, Support Vector Machine (SVM), C5.0, Naive Bayes, and Artificial Neural Networks for prediction analysis, and made a comparison between these algorithms. View Full-Text
Keywords: HCI; Healthcare Big Data; cloud; HPC; MapReduce; data warehouse HCI; Healthcare Big Data; cloud; HPC; MapReduce; data warehouse
Show Figures

Figure 1

MDPI and ACS Style

Bhuiyan, M.A.R.; Ullah, M.R.; Das, A.K. iHealthcare: Predictive Model Analysis Concerning Big Data Applications for Interactive Healthcare Systems . Appl. Sci. 2019, 9, 3365.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop