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              <text>Machine Learning Observation on the Prediction of Diabetes Mellitus Disease</text>
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              <text>Diabetes; Machine Learning; Prediction; Training Model</text>
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              <text>Diabetes disease has become as one of the common syndromes in many of the age groups. Diabetes can result in high blood sugar levels, a heart attack, or heart disease. This is one of the fastest developing illnesses, and it requires regular care. After seeing the doctor and being diagnosed, the patient is typically compelled to obtain their reports. Because this procedure is time-consuming and costly, we have the option of using ML approaches to solve this problem. Our research aims to foster a framework prepared to do all the more precisely foreseeing a patient's diabetes risk level. To develop models, classification methods such as Logistic Regression, K-Nearest Neighbor, Support Vector Machine, and Random Forest Classifier are employed. The results indicate that the techniques are quite accurate. The result showed that the prediction with the Logistic Regression model acquired the highest accuracy.   2023 IEEE.</text>
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          <name>Creator</name>
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              <text>Kumar P.D.; Priya S.L.; Kumar K.P.; Rego A.M.</text>
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              <text>Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications</text>
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          <name>Publisher</name>
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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/InC457730.2023.10263082" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/InC457730.2023.10263082&lt;/a&gt;
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          <name>Rights</name>
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              <text>Restricted Access</text>
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              <text>ISBN: 979-835033577-4</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Kumar P.D., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India; Priya S.L., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India; Kumar K.P., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India; Rego A.M., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India</text>
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