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All Journal Journal of Intelligent Decision Support System (IDSS)
Hanna Willa Dhany
Universitas Pembangunan Panca Budi, Medan, Indonesia
Computer Science & IT

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Exploratory Data Analysis (EDA) methods for healthcare classification Hanna Willa Dhany; Sutarman Sutarman; Fahmi Izhari
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 4 (2023): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v6i4.165

Abstract

The recovery and rehabilitation of individuals, helping them regain their physical and mental well-being. Healthcare offers comfort and relief for patients with serious or terminal illnesses, focusing on improving their quality of life and managing symptoms. It plays a role in educating individuals about health risks, disease prevention, and healthy lifestyles. Healthcare contributes to medical research and innovation, leading to advancements in treatments, medications, and medical technologies. Here are some common results and findings that can be obtained through EDA in healthcare data about EDA can reveal the age, gender, and other demographic information of patients. This information is essential for understanding the population served by a healthcare facility. EDA can help identify the prevalence of different diseases or conditions within a patient population. This can assist in resource allocation and healthcare planning. EDA can show how disease rates or healthcare utilization patterns change over time. For example, it can highlight seasonal variations in the incidence of certain diseases. EDA can be used to analyze healthcare data geospatially to identify regions with higher disease prevalence, helping in targeted interventions.
Co-Authors Fahmi Izhari Sutarman Sutarman