Mar 8 2019

Computational Collaboration to Expand Care to Remote Populations

Dr. Karen Yeates, Associate Professor, Queen’s University

In conversation with Dr. Karen Yeates, Associate Professor, Queen’s University

Can you tell us about your work?

I was funded by GrantChallenges Canada to scale our cervical cancer screening project in Tanzania. This work was carried out in collaboration with Tanzania’s Ministry of Health and their National Cervical Cancer Screening Program to train nurses to do a visual inspection of a woman’s cervix using an app call Servical. The program is now called Smartphone Enhanced Visual Inspection with Acetic Acid, or SEVIA. The app has a monitoring and evaluation dashboard which helps experienced peer mentors/supervisors review cervical images and give advice and supervision on-the-ground health-care workers. We also use this to rapidly train nurses to develop skills to do screenings anywhere.

We now have over 100,000 images in our database with the goal of working with global partners in developing an AI application to be able to say if a lesion is cancerous or not. The long-term applications for medical care in remote locations in East Africa, Canada and around the world are very promising.

Did you always know this is what you want to do?

No – I am actually nephrologist, a kidney specialist, by training and I initially worked extensively with indigenous populations across Canada. I went to Tanzania in 2006 to help with some logistics for an HIV program. Even though the setting was different, it felt like their challenges were very similar to those I faced while working in remote indigenous communities in Canada.

While working on a kidney program for the International Society of Nephrology, I realized a number of young women who came in for kidney treatments had advanced cervical cancer. This cancer was the reason they had kidney failure as the disease had invaded their pelvis. These women were incurable, and there was nothing we could do for them.

The Tanzanian government had a program that involved training nurses in using a visual inspection method. One day as I was checking my phone in 2011, I thought we could train nurses across Tanzania if we used a phone to send the image of the cervix to a professional who could review them and give advice and supervision. After a brief test period, we found that it worked! We screened over 10,000 women in the first year and started to expand the program to other countries. The project has grown multifold ever since.

What role does advanced research computing (ARC) play in your research?

I am grateful to have found the Centre for Advanced Computing at Queen’s University. I do mobile health research, and we can’t do everything by ourselves. People are experts at different things, and it’s a marriage of these different sets of expertise. The staff at CAC thinks of things that I would have never thought of or know that I needed it. I think it is wonderful from a global collaboration perspective as well. Technology helps us bridge the gaps in humanity.