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- W4310257702 abstract "Nowadays, machine learning plays a significant role in healthcare system, medical information, and identification. This technique also uses understanding of several significant medical issues, such as diabetes projection, heart observation, and coronavirus identification. Machine learning is one of those tools that is commonly used in many fields because different datasets do not require different algorithms. Machine Learning is a subset of artificial intelligence. Machine learning can be a superior option for reaching high performance in predicting CKD and useful for other diseases, as this technique uses selected features and their different types of data forms under different conditions to predict CKD. Here, in this study, comprehensive survey of ten studies is presented where different machine learning models are compared for their efficiency and accuracy. The main aim of this study is to observe and analyze various machine learning models used, also to explore the datasets used, pre-processing techniques used, feature selection techniques used and to compare these models to find out which model provide us the best results. The study can help in smooth implementation of the work in the future which can be further to get the best possible result. In this study, machine learning can be a solution to this problem as it performs best in detection and evaluation using an algorithm. During this study, it was found that the filter feature selection methods used with correct threshold value which is suitable for dataset, it provides best accuracy over other feature selection method and also, any model dataset acquired before training needs to be pre-processed. The main goal of existing papers is to investigate, design and develop machine learning depend prediction model for CKD and to design a model to analyze and represent the knowledge of the field." @default.
- W4310257702 created "2022-11-30" @default.
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- W4310257702 date "2022-11-25" @default.
- W4310257702 modified "2023-09-27" @default.
- W4310257702 title "Machine Learning-Based Algorithms for Prediction of Chronic Kidney Disease: A Review" @default.
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- W4310257702 doi "https://doi.org/10.1007/978-981-19-5292-0_21" @default.
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