Detecting diabetes using machine learning techniques and python GUI.

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    • Abstract:
      Diabetes is one of the deadly diseases in the world. Because of diabetes, several varieties of disorders may occur in the body, like blindness, urinaryorgan failure, etc. As such case patient needs to visit clinical labs toget their reports after consultation. Due to this, every time, they have to invest their time and currency. The explosive growth of health-related data presented unprecedented opportunities for improving the health of a patient. Machine learning plays an essential role in the healthcare field and is being increasingly applied to healthcare. The proposed model helps to develop a system that predicts the diabetes risk level of a patient in the early stage itself without visiting any clinical labs with an accuracy of 80.5%. Datais collected from Pima Indians Diabetes Dataset (PIDD). Model development is based on the Support Vector Machine algorithm. Also, in this proposed method, the patient's risk level will be predicted with the helpof symptoms which is experiencing, and based on that report is generated. [ABSTRACT FROM AUTHOR]
    • Abstract:
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