Thyroid Disease Detection with Future Prediction and Food Suggestion using ML Algorithms || VIP |HYD

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About Project:
Every year worldwide millions of peoples are affected with thyroid disease and unattended or late diagnosis may worsen this disease and for timely prediction we are employing and evaluating performance of various machine learning algorithms such as SVM, Naïve Bayes and Random Forest and in all algorithms Random forest is giving best performance with an accuracy of 95 to 99%.
Extension Concept: ML algorithms will predict whether patients are Positive or Negative, upon negative prediction then in future patients may generate symptoms of thyroid so we are measuring current Thyroid TSH level and then comparing this TSH current level with closest thyroid levels which may fall in next few days to several weeks or months. If detected TSH level is in between 0 and 0.4 then patients may get thyroid in next month, if range between 0.4 and less than 10 then it may take next 3 month and above TSH 10 may take next 1.5 to 6 months