At ZS, we know curiosity fosters innovation. By encouraging ZSers to ask hard questions, we can better collaborate and find new solutions. This is true for all the work we do but especially for Helena Deus, a data science manager working to bring artificial intelligence (AI) to healthcare.

 

Helena started her career as a computational biologist, spending nearly two decades working with organizations to better understand cancer. “I’ve always had a deep curiosity around what drives this disease,” she says. “Why is it still a problem after so many attempts to eliminate it and what can be done about it?” There are no easy answers for questions like these. With some creative thinking, Helena hypothesized that pieces of the answer already exist, they just need to be collected and connected. Through her work at ZS, Helena creates AI-based solutions that can be used to assist in cancer treatment.

Helena lights up when talking about her work and the many ways she is changing lives. “I am excited about what scientists will be able to do once AI takes care of the repetitive and systematic work,” she says. “Oncologists and biomedical scientists need to research hundreds of medical records to understand how other patients responded to certain sequences of treatments. Instead, AI provides an opportunity to scale this research and give scientists time to focus on breakthrough discoveries and innovation.”

Helena and her ZS colleagues partner with healthcare organizations to solve some of the most impactful and complex challenges in AI. When reflecting on the work she is most proud of, Helena remembers collaborating with other ZSers first.

 

“My team and I partnered with a client to address the target discovery problem for a complex inflammatory disease which is common but not fully understood,” she says. “Different patients seem to respond differently to treatment. Through brainstorming and collaborating with the client and my team, we began to wonder if different cohorts might respond differently because the underlying biology is different. If we could find out the patients with common biology, we could treat each subgroup individually based on the cluster of symptoms that they presented.”

 

To test this theory, Helena and her team first needed to map the symptoms to the biological explanation. Using two AI tools, weak supervised machine learning and knowledge graphs, the team inferred the biological mechanisms that explained the symptoms, helping the client prioritize the treatments that might work best for individual groups of patients.

“I am very proud of the quality and discipline that the data science teams at ZS bring to everything we do,” Helena says. Staying true to our innovative culture, ZS knows that the greatest impact of AI can only be realized if it evolves as new types of data emerge. To realize that value, ZS teams invest time and energy learning about and experimenting with the latest tools, technologies and data sets to understand their potential and limitations.

 

To find your passion and join the team in innovating AI, explore our open roles.

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