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              <text>Enhancing Disease Prediction in Healthcare: A Comparative Analysis of PSO and Extreme Learning Approach</text>
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              <text>Disease Prediction System; Extreme Learning Machine (ELM); Particle Swarm Optimization (PSO)</text>
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              <text>The healthcare business generates a tremendous quantity of data, and the goal is to collect it and use it effectively for analysis, prediction, and treatment. The best approach to disease management is disease prevention through early intervention. There are a number of methods that can advise you on how to treat a specific sickness, but much fewer that can tell you with any degree of certainty if you will actually get sick in the first place. Preprocessing, feature selection, feature extraction, and model training are all parts of the proposed method. The suggested layout includes a preprocessing stage that takes care of things like moving average, missing values, and normalization. Feature selection describes the process of selecting the most relevant features from a dataset. After gathering features, the models are trained using PSO-ELM. The proposed strategy is superior to the widely used PSO and ELM.   2023 IEEE.</text>
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              <text>Prabakaran M.; Bhole M.K.; Kalpana V.; Dixit S.; Divya K.; Chauhan D.A.</text>
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              <text>3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023 - Proceedings, pp. 1092-1097.</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>2023-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1109/ICIMIA60377.2023.10426121" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICIMIA60377.2023.10426121&lt;/a&gt;
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              <text>ISBN: 979-835034363-2</text>
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              <text>Online</text>
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              <text>Prabakaran M., Madanapalle Institute of Technology &amp;amp; Science, Department of Computer Science and Engineering (Data Science), Andhra Pradesh, India; Bhole M.K., Bharati Vidyapeeth College of Engineering, Department of Instrumentation Engineering, Navi Mumbai, India; Kalpana V., RMK College of Engineering and Technology, Puduvoyal, Department of Science and Humanities, Tamilnadu, Thiruvallur, India; Dixit S., Vellore Institute of Technology, School of Computer Science Engineering, Tamilnadu, Vellore, India; Divya K., Prince Shri Venkateshwara Padmavathy Engineering College, Department of ECE, Chennai, India; Chauhan D.A., CHRIST (Deemed to Be University), School of Sciences, Department of Life Sciences, Karnataka, Bengaluru, India</text>
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