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Analyzing the impact of data visualization applications for diagnosing the health conditions through hesitant fuzzy-based hybrid medical expert system.
- Source :
- Ain Shams Engineering Journal; May2024, Vol. 15 Issue 5, pN.PAG-N.PAG, 1p
- Publication Year :
- 2024
-
Abstract
- Effectively managing healthcare data is crucial for accurate diagnosis and personalized patient care. As the utilization of healthcare data grows for personalized care, concerns about reliability, privacy, and security have emerged. To address these issues, this research explores the fusion of analytical techniques with interactive visual representations, known as visual analytics, as a promising solution. The focus is on evaluating the trustworthiness of healthcare data in Kingdom of Saudi Arabia, particularly the capability of visual analytics tools in facilitating accurate and secure healthcare data analysis. This study tackles challenges such as the absence of specific evaluation criteria, the need to process vast healthcare datasets, the establishment of trust, and the necessity for automation. In response, a hybrid medical decision support system is introduced, leveraging hesitant fuzzy decision systems. The primary objective is to evaluate trustworthiness of visual analytics tools for disease diagnosis within healthcare data. Within the framework of hesitant fuzzy logic, the paper employs a medical multi-criteria decision-making system that integrates the analytic network process and the technique for order of preference by similarity to an ideal solution. Rigorous validation ensures the accuracy and reliability of the findings. The research not only provides valuable insights but also conducts comparative analyses of the proposed models against existing ones, demonstrating the practicality of optimal decision-making in Saudi Arabia environment of healthcare scenarios. Several popular alternatives of healthcare based tools have been used in this study such as Tableau, JupyteR, Zoho Reports, QlikView, Visual.ly, DOMO BI, SAS Visual Analytics. From the results achieved DOMO BI visual analytics tool is found to be most secure and robust tool for healthcare professionals. This effort aims to enhance patient care and outcomes, ultimately contributing to the improvement of the overall healthcare landscape in Saudi Arabia. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20904479
- Volume :
- 15
- Issue :
- 5
- Database :
- Supplemental Index
- Journal :
- Ain Shams Engineering Journal
- Publication Type :
- Academic Journal
- Accession number :
- 176866488
- Full Text :
- https://doi.org/10.1016/j.asej.2024.102705