Johann Vargas Calixto uses AI tools to make pregnancy monitoring more accessible.
Johann Vargas Calixto is a postdoctoral researcher at Emory University is using machine learning to track fetal growth restriction and preeclampsia throughout pregnancy. In this Postdoc Portrait, he shares why it is important that these algorithms remain low cost so that they remain available in rural indigenous communities in Guatemala.
Q | How did you first get interested in your field of research?
As a kid, it was always my dream to build robots. I pursued a bachelor’s degree in mechatronics engineering, but I found that I was more interested in biomedical engineering and decided to do an Meng focusing on biomechanics. After I started my PhD, I realized that I had nostalgia for my country of origin, Peru. I felt that my work would not benefit countries like mine. Around this time, I was visiting Peru and fell ill while in a northern rural town. In the community health center, I experienced firsthand the limitations of our health system. Moreover, I saw how a distressed pregnant woman, whose baby’s heartbeat they could not find, had to wait for an ambulance to take her to the nearest town with an ultrasound machine—a two hour ride. This experience completely changed my perspective: I wanted to help improve maternal-fetal health in pregnancy, particularly in low-resource settings. Thus, I changed PhD projects to specialize in maternal-fetal health. After my PhD I searched for a postdoctoral position that could help me use the skills I learned to help people with less resources which are the most vulnerable.
Q | Tell us about your favorite research project you’re working on.
Most monitoring devices, which we take for granted in the US, are not available in low-resource settings. The main limiting factors are the high costs and need of highly specialized operators. My current research is part of a larger project, which has integrated a low-cost Doppler ultrasound device (about $10), a blood pressure monitor, and a smartphone app. This project has been successful in reducing maternal mortality in rural indigenous communities in Guatemala. So far, the analysis of the Doppler sounds has been focused on the analysis of the fetal heart rate throughout pregnancy. However, these sounds contain much more information than the heart rate of the fetus. If we knew the target of the sounds, we could develop targeted algorithms that extract physiological-relevant information from fetal-maternal structures. Tracking these variables throughout pregnancy would help us understand how fetal and maternal hemodynamics evolve in pregnancy, and when they are indicative of severe complications such as fetal growth restriction or preeclampsia. I am currently developing an automated algorithm that can first differentiate between the sounds coming from the umbilical cord and the fetal heart. In the future, this classifier could be expanded to also recognize placental and maternal blood vessels.
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Q | What has been the most exciting part of your scientific journey so far?
The feeling that what I am currently doing matters and that it can help people that really need it has been the most exciting and motivating part. Furthermore, it is extremely gratifying to know that my work is directly applicable to Latin America, including Peru. While I have enjoyed the whole journey, the feeling of helping others is unparalleled. Also, I have participated in many international conferences, and I have met a lot of wonderful people with a similar career goal. Having this community of colleagues that are motivated by the same dream has been a very nice experience, which has reinforced my feeling of satisfaction and hope in the work I do.
Q | If you could be a laboratory instrument, which one would you be and why?
I am part of a biomedical informatics lab, so we do not have many instruments besides computers. However, there is another piece of equipment that is crucial to our work: the espresso machine. Thus, I would like to be the espresso machine. This little machine gives everyone the energy that they need for their long days running experiments and writing grants. Similarly, I hope to one day be able to motivate others to continue working to achieve their career goals. Also, the best coffee I have tasted comes from Peru, which is another reason the espresso machine relatable.
Responses have been edited for length and clarity.
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