In Conversation: Emmanuella Budu (PhD Candidate, Machine Learning in Healthcare)

As a doctoral student at Halmstad University in Sweden, Emmanuella's research work is centred around the intersection of machine learning and healthcare. In this interview, she takes us through her early fascination with technology, the intricacies of her research work, as well as her thoughts on the potential impacts of machine learning on healthcare.

In your own words, please tell us who Emmanuella Budu is

Emmanuella Budu is a lifelong student, data enthusiast, doctoral student, sister, friend, daughter, and a Christian. 

Please take us through your career journey in tech

My journey started by pursuing a Computer Science education in high school and at the University of Botswana. At the University of Botswana, I was also involved with development communities such as WIMLDS Gaborone and PyDataBW, which helped me develop my programming skills in machine learning. In 2020, I underwent Data Science mentorship programs at Zindi and SheCode Africa, where I learnt how to apply machine learning to solving real-life challenges. I worked as a Research Analyst at Abeyie Innovation Studios on their Traffik Alert project, a project aimed at using predictive analytics to fight human trafficking. I have also worked as Research Assistant in machine learning at the University of Botswana. I am currently a doctoral student at the Center for Applied Intelligent Systems Research (CAISR) at Halmstad University in Sweden, where I work at the intersection of machine learning and healthcare.

What inspired you to pursue a career in tech?

From a very young age, I was fascinated by computers and automated devices. This is what influenced me to take up Computer Studies in high school. During my undergraduate studies, I became interested in data mining and machine learning. Particularly, how you can derive so many insights from data by just applying a few algorithms. Subsequently, I took a keen interest in the application of machine learning in the real-world space, particularly, in health, crime, etc.  All these have led me to where I am now. 

Please tell us what your current role entails

I currently work on generating synthetic Electronic Health Records (EHRs) using generative models. EHRs contain time-sequenced information about the health history of patients and their encounters with a healthcare provider. However, there are strict restrictions on the use of this data due to data protection laws and regulations. 

Developing solutions with machine learning in healthcare is data-hungry like any other field. The goal of my work is to address this challenge by using generative models to create high-fidelity synthetic EHRs that resemble real EHRs to speed up and facilitate innovation and research in the field.

Your research work involves the use of machine learning in healthcare. How important do you think such technologies can play in accelerating healthcare on the continent?

I believe machine learning and AI, in general, has the potential to transform healthcare systems on the continent by enhancing disease diagnosis, treatment options and improving service delivery. Imagine an environment where clinicians are equipped with Clinical Decision Support Systems to aid their assessment of patients. Imagine diagnosis systems built on top of machine learning that help with the early detection of diseases hence reducing mortality rates. The benefits of AI in healthcare are many.

What challenges do you think are impeding the adoption of such technologies on the continent?

The development of such solutions is greatly hindered by access to data. Machine learning models are data-hungry because they learn from existing data to give output. Therefore data is needed to drive efforts in the development of healthcare solutions. Without this, these efforts are limited.

How can such challenges be addressed?

I think the first step to addressing this challenge is to make data more accessible to innovators, developers and researchers. We need to put efforts into creating open data repositories to allow the free flow of data between data custodians and innovators, researchers and developers. I believe making this possible is a step in the right direction.

What is your favourite part about the work that you do?

I love how flexible the work is. I have the freedom and time to explore different algorithms and techniques to see what works and what does not work. 

What is the most challenging aspect of it?

The most challenging aspect of it is how fast the field is progressing. It's almost as if there is a new model being developed every month. This is not entirely negative because it keeps you on your toes, meaning, you always have to be up to date with new algorithms and techniques.

What has been the proudest moment of your career so far?

Sharing my work with others on international platforms such as conferences is always a proud moment for me. This tells me that the work I am doing is worthwhile. It pushes me to keep on doing what I do. 

What’s something you know now that you wish you knew earlier in your career? 

Maintaining a good work-life balance is key. In my early years, I always prioritized my work and school and did not make time to engage in any social activities. I realize now that there is time to work and there is time to focus on building your personal life. 

If any, what is the best advice you have received in your career? 

You always have to reinvent yourself. I think this is true for almost everyone regardless of whether you work in tech or not. You have to allow yourself to learn and pick up new skills, embrace new technologies, change your thinking, invest in yourself, and take risks.

Careerwise, where do you see Emmanuela five years from now

Five years from now, I see Emmanuella actively involved in the development and implementation of solutions that advance the use of machine learning and AI technologies in the health sector. 

What advice would you give to young girls looking to pursue a career in tech?

Just go for it! We need more women in tech. Identify where your interests lie and flourish there. 

Interview has been edited for clarity.
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