Abstract
The number of factors that can be categorized into the diagnosis of Chronic Kidney Disease (CKD) at an early stage makes information about the diagnosis of the disease divided into information that has many influences and has little influence. This study aims to select diagnoses in medical records with the most influential information on chronic kidney disease. The first step is to select a diagnosis with much influence by implementing the Sequential Backward Feature Selection (SBFS). This algorithm eliminates features that are considered to have little influence when compared to other features. In the second step, the features of the best diagnoses are used as input to the Artificial Neural Network (ANN) classification algorithm. The results obtained from this study are information in the form of the best diagnoses that have much influence on chronic kidney disease and the accuracy results based on the selected diagnoses. Based on the study results, 15 features are considered the best of the 18 features used to achieve 88% accuracy results. Compared with conventional methods, this method still requires consideration from the medical staff because it is not a final diagnosis for patients.
Highlights
The increase in the number of patients suffering from Chronic Kidney Disease (CKD), which continues to occur every year, makes this disease one of the diseases included in a global public health problem
Types of strategies for using Sequential Feature Selection include [3]: (1) Sequential Forward Feature Selection (SFFS), which selects features based on "forward" sequential search strategy; (2) Sequential Backward Feature Selection (SBFS), which works the opposite of the SFFS method; (3) PlusL Minus-R Selection (LRS), which is considered as an integration between the SFFS and SBFS methods
Based on the study conducted, it can be concluded that the selection of diagnostic features of chronic kidney disease can be made by implementing the SBFS method
Summary
The increase in the number of patients suffering from Chronic Kidney Disease (CKD), which continues to occur every year, makes this disease one of the diseases included in a global public health problem. The level of the condition in patients with chronic kidney disease varies. When the disease has been acknowledged and detected early, the risk of complications and the risk of worsening the condition of patients suffering from these diseases can be reduced. Medical treatment will immediately be carried out based on the early diagnosis that occurred in the patient. Diagnosis is an activity that has to do with collaboration between clinical reasoning and information gathering to determine health problems experienced by patients [1].
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