A filter-based machine learning classification framework for cloud-based medical databases. (14th June 2022)

• Record Type: Journal Article
• Authors: Sri, V. Devi Satya; Vemuru, Srikanth
• Is Part Of: International journal of ad hoc and ubiquitous computing. Volume 40:Number 1/3(2022)
• Page Start: 94
• Page End: 105
• Publication Date: 2022-06-14
• Subjects: medical databases -- machine learning -- cloud computing; Ubiquitous computing -- Periodicals; Embedded computer systems -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Wireless communication systems -- Periodicals; Computer architecture -- Periodicals; 004.2
• Languages: English
• ISSNs: 1743-8225

Abstract

Machine learning tools and techniques play a vital role in the medical field and cloud computing applications. Most of the traditional machine learning models use static metrics, limited data size and limited feature space due to high computational processing time. In this work, a hybrid outlier detection and data transformation approaches are implemented on the cloud-based medical databases. Proposed data filtering module is applicable to high dimensional data size and feature space for classification problem. In the classification problem, an advanced boosting classifier is implemented on the filtered data in order to improve the true positive and error rate. Experimental results are simulated on different medical datasets such as tonsil and trauma databases with different feature space size and data size. Simulation results proved that the proposed boosting classifier has better error rate and statistical accuracy than the conventional approaches.