Quantum-powered Cataract Detection : Learn Quantum and Save Eyes
Welcome to the Womanium-CataraQt repo
Description and objectives
Womanium CataraQt is a Quantum Machine Learning project for remote and reliable detection of cataracts, inspired by the Womanium Global Quantum Program.
This project aims to employ a mix of Quantum and Classical Machine Learning techniques to detect the presence of cataracts from eye images, without continual medical intervention or specialized optical equipment. Quantum Classical Convolutional Neural Networks, Quantum Support Vector Machine and Hybrid Quantum feature selection algorithm are some candidates for implementation and performance assessment.
Cataract is documented to be the major cause of avoidable blindness in India, accounting for nearly 50% of the bilaterally blind here. Elsewhere in the world, too, the situation is similar. 10 million is the number of cataract blind people in India in 2020, with an annual incidence of 4 million, as per surveys and estimates. If the disease is detected faster, remotely and reliably, scarce medical resources could be reallocated more efficiently for surgical intervention and improved quality of life in not-so-developed rural areas.
Another equally important objective of this project is Quantum Outreach. Come and learn with us! We provide annotated datasets of eye images, easy-to-follow tutorials on quantum basics, links to training material, tools and sample software modules as well as one-on-one guidance on writing your QML program.
Thank you @WOMANIUM for starting us on our quantum journey and enabling this exciting open-source project!
Contributing
We are excited to work alongside you. Feel free to contribute and make a social impact !
Communicating with the Team
Communicate with the team via GitHub issues.