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AI-notes

These notes were initially taken while conducting my engineering final year project. Design an in-house intelligent medical device (sensors included !) to ease the Therapeutic Patient Education (TPE) process, applied for Diabetes disease.

The idea here is to develop an AI ChatBot, connected with a predictive trained model(ML) hooked through my domain to provide instant Telegram responses served from implemented flask framework !

  • The ChatBot has mainly 2 essential functions:
  1. provide educational materiels for patients with diabetes disease. (customized Telegram responses)
  2. monitor predictive measures for non-diabetes persons.
  • Faced 2 main branches of AI :
  1. Natural Language Processing (NLP) especially the classification ! (intent classification)
  2. Machine Learning, predictive analytics. (Diabetes prediction)

Notes

  • DialogFlow was chosen for Implementing our ChatBot as DRY principle, and also to avoid processing hasle !
  • This will be updated as I go through AI :)
  • Notes aren't well structured, but yet well used !

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