During the past year and a half, the world has witnessed a raging pandemic that has forced countries to implement lockdowns in order to combat the spread of Covid-19. Taking precautions meant, people were confined to their homes for the most part which has resulted in them hesitating to visit hospitals for regular health checkups. During the pandemic, our immunity is of utmost importance and signs of health deficiency should not be ignored. But having said that people hesitate to visit hospitals to conserve time and for their safety, a tool to facilitate these regular health checkups was essential.
Our concept is to develop a smart application that people can use to identify any health deficiencies that they might potentially have by taking photos of your body parts. The application will utilize a pre-trained artificial intelligence model (Convolutional Neural Network) to analyze the photos and identify certain characteristic features to diagnose any potential health deficiency. If any health deficiency is identified, the smart app will also provide appropriate diets to increase the amount of a particular vitamin/mineral in the body to the optimum level.
• Develop the CNN model to identify the characteristic features
• Train and optimize the developed neural network
• Prototyping the smart application
- Machine Learning
- Neural Networks (in particular Convolutional Neural Network)
- Feature Extraction
- Data Classification
- MATLAB
What is a Convolutional Neural Network: https://www.mathworks.com/discovery/convolutional-neural-network-matlab… [1]
MatConvNet - Convolutional Neural Networks for MATLAB: https://www.researchgate.net/publication/269636298_MatConvNet_-_Convolu… [2]