Telling the difference between typical and atypical optic neuritis is hard.

OpticKey makes it easy. Our dedicated deep-learning model will ensure you never have to second-guess yourself, giving you and your patient the peace of mind you deserve.

Clinical judgement alone has proven to have a 60% misdiagnosis rate between typical and atypical cases of optic neuritis.

The future of a patient's vision depends on an accurate and prompt diagnosis, which calls for 21st century tools

What does our project entail?

A deep learning artificial intelligence system utilizing ocular fundus photographs to differentiate between typical and atypical optic neuritis classifications.

How do we plan on doing this?

We plan on taking a dataset with known classifications and running those images through the model to see the sensitivity and specificity of our model as measured by receiver operator characteristic curves. This would give us an ideal of how often we are producing false positives and false negatives and use that to guide our optimization process moving forward.

What diagnostic accuracy are you aiming for?

We propose that a rate of minimal 65-70% diagnosis accuracy would be considered successful for the purpose of this competition. We plan on continuing after the completion of this competition and would ideally like to reach a state of 90%+ diagnostic accuracy.

How can you help?

We were hoping that you, as an experienced physician, would be able to give us some insight about the patient care and patient outlook aspects of our project. We would love to have a short 30-minute discussion to hear your observation and understanding about this topic.

Who we are.

We are a group of humans with a shared goal

Nuha Shaikh

Software Engineer

Hello everyone! My name is Nuha and I am currently in my second year of Software Engineering with a minor in Biomedical Engineering at the University of Calgary. I have always had a passion for learning more about biology, specifically human anatomy, thus, I am hoping to bridge my interest in biology and my knowledge about programming through working with OpticKey, hopefully making it my career throughout my life.

Jordan Bird

Health Sciences Reseacher

My name is Jordan and I am a BSc Health Science graduate from Mount Royal University. I got my start in research in 2018 with environmental physiology and have not looked back. If all goes well, I hope to one day be a research physician in ophthalmology.

In my free time, I play hockey, write papers, and read whatever book or scientific paper I can get my hands on.

Abdul Syed

MD Candidate

My name is Abdul! I am a first-year medical student at the University College Dublin from Calgary, Canada. I’m interested in bringing healthcare and technology together to improve patient outcomes and experience.

In my free time, I am a freelance photographer and enjoy reading.

Lubaba Sheikh

Software Engineer

My name is Lubaba! I am a second-year software engineering student with a minor in biomedical engineering at the University of Calgary. I am interested in learning more about AI technology and machine learning.

Kevin Zhan

Second-year Science Student

Hi everyone! I'm very excited to be on this team of very knowledgeable people. My name is Kevin and I'm in my second year of a Sciences degree at U of A. I am very interested in machine learning and deep learning models. I hope to learn alot from this competition!

Daniel

Software Developer

My name is Daniel, I am software developer graduated from University of Calgary. I am interested in closing the gaps between medical and technological fields. I am interested in Machine Learning and Extended Reality technologies.

Chris Schultze

Computer Scientist

My name is Christopher and I am in my third year studying to get a BSc in Computer Science with a concentration in Software Engineering at the University of Calgary. I am interested in programming, artificial intelligence and computer networks, and think that applying logic with neuroscience is fascinating.

Contact us

Got any questions? Don't hesitate to reach out.

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