This month we are pleased to feature PhD candidate Natasa Lazarevic.
Please tell us a little bit about yourself.
Hello, I am Nataša (pronounced Natasha). I have been fortunate enough to live in 5 different countries, but that also means that I find the concepts of my nationality, identity and sense of belonging hard to understand. According to my passports, I am both Australian (as of recently!) and Serbian but I was born in Germany, then lived in Serbia, grew up in Botswana for most of my childhood, then the United Arab Emirates for my teenage years and now I live in Australia. I’ve learnt that our sense of culture and identity is so much more than what our passports reveal.
I completed my undergraduate degree in Medical Science at the University of Sydney in 2016 and then took a gap year to travel and work. I started working as a curriculum coordinator/designer in the School of Medical Sciences as well as for the Body Donor Programme. In 2018, I completed an honours degree in immunology, after which I realised that I wanted to pursue more interdisciplinary and translational work, and this led me to a project I did as a part of my Charles Perkins Centre Summer Scholarship. I fell in love with the work and decided to continue the work as a PhD researcher.
While completing my PhD, I am also a casual academic tutor in the discipline of Anatomy and Histology. I teach both undergraduate and medical students and enjoy it thoroughly. Everything about our bodies and how they work fascinates me.
What is your research on?
I work on an interdisciplinary project that combines the fields of digital health, machine learning and anatomy. The project is about applying our understanding of the human body to create technological solutions to monitor our bodies and our health remotely.
Changes in body shape and size can reflect adaptive and maladaptive changes in our overall health. Pregnant women are a particularly relevant population in this regard. Monitoring body changes as well as overall health are vital during pregnancy as specific changes in weight distribution can indicate the development of secondary conditions such as gestational diabetes and obesity, pre-eclampsia or the need for a caesarean delivery (Padmanabhan et al., 2015). Building novel digital health tools has great potential to improve the health and gestational weight management of pregnant women.
The ultimate goal of my research is to use the technology already built into our phones (such as cameras) and computer vision techniques to build a ‘Pregnancy App’ that gathers health-relevant data from the users. The software, which we have started building, will recognize the outline of the body or region of interest in the image to identify and quantify body changes over time. Users will then have an option to share their health-related results to their chosen healthcare professionals. Machine learning technology will provide tailored information and advice to the user and will also help healthcare professionals make decisions about appropriate healthcare or treatment.
However, before we start building a pregnancy app, we plan to interview and survey pregnant women and healthcare professionals to better understand their needs and identify existing gaps in self-monitoring during pregnancy.
What are the real-world consequences of your research?
The increase in access and use of mobile apps offers an opportunity to transform and improve current health monitoring systems, especially for people residing in remote areas or disadvantaged communities. The pandemic this year has demonstrated just how important it is to be able to monitor health remotely now and in the future. Our app solution will also offer an opportunity to empower pregnant women to self-monitor their health and wellbeing during this important time.
Moreover, building a pregnancy app that will include such a collection of anonymised data from both pregnant women and healthcare professionals will allow for the app software to evolve and learn with the users over time. This will enable identification, prediction and prevention of pregnancy-related health outcomes. For example, identifying the development of obesity during pregnancy will help to predict the likelihood that a user will become prediabetic. Importantly, we plan to design the app with ongoing user feedback, who come from diverse backgrounds, to ensure no user is left behind.
What does digital health mean to you?
To me digital health is about harnessing technology to improve people’s wellbeing. Digital health tools have the potential to enhance the efficiency of healthcare delivery and allow for health-related information to be shared securely across healthcare sectors. I envision that as a community we can develop a digital health ecosystem that integrates national platform services and has the capacity to support users at a large scale. I am hopeful that digital health initiatives can lead to economic growth and overcome the limitations of physical infrastructure, especially in rural areas, underrepresented communities and developing countries.
Do you have any resources or links you would like to share?
I am also passionate about promoting the equality of underrepresented groups in STEM so I co-founded Visibility STEM Africa (VSA – @ViSTEM_Africa) with my dear friend Nathasia Mudiwa Muwanigwa (@Tasia1409). VSA promotes the visibility of Africans in STEM and provides them with opportunities to flourish.
A huge thank you to Natasa for taking the time to be our October Research Student profile.