Keywords: Diabetes, prediction
Deep learning techniques are one of the major evolving technologies in the current trend and their applications are spreading rapidly across all the different fields. ANN is one of the major techniques in Deep learning and it has a good scope to be involved in the analysis of the medical data. ANN is a kind of neural network, and it has tried to develop a neural network that is like that of humans. It has made several different connections within the layers by involving several different perceptrons. Prediction in the medical field needs to be accurate as the wrong predictions can lead to severe impacts and there might be a loss of a person’s life. Applying ANN will help in predicting the results in a desired manner as it has an in-depth understanding of data through the usage of different activation functions and aggregate functions. Overall, after a thorough application of ANN of diabetes data, the author has achieved desired results and created a good model for predicting diabetes in humans.
Aim
To Predict a person having Diabetics or not using DL Techniques
Objective
Implement an ANN model to accurately predict diabetes, aiding early detection and personalized healthcare.
Develop an ANN system that analyzes medical data to forecast diabetes risk and potential onset.
Evaluate the ANN's prediction accuracy, contributing to effective diabetes prevention and management strategies.
ANN Technique used
Jupyter, Google Collab
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