Creating value for clinicians and patients using data science

Rianne Fijten, a data researcher at Maastro Clinic, has a background in biomedical sciences but never really enjoyed lab work. “I’m quite an impatient person and enjoy tinkering, which does not lend itself well to lab experiments. Unlike data science, which relies on large datasets and AI to develop data models and predictions.” 

During her master’s in Biomedical Sciences at Maastricht University, Rianne got acquainted with data sciences and specialised in it later on, with a doctorate in breathomics, a non-invasive method to detect various types of cancer in exhaled human breath. “And there is the benefit of data science, clear and simple. Generating results quickly to gain insights into biological mechanisms and then using literature or the lab to continue with those insights.” 

Rianne works at Maastro Clinic where she strives for the clinical implementation of data science. “We’re in close contact with the medical staff and patients at Maastro to ensure our research is clinically logical, valuable and empowers patients.” One example Rianne provides is using AI models to help prescribe medication for patients. “Instead of trial and error, a burden for the patient, we use existing data to predict which medication works from the start for an individual patient, with side effects minimised.”  

The healthcare sector is still somewhat resistant to working with AI, but times are changing. “AI has become mainstream; we notice the same shift in healthcare. Hopefully, this means that our research projects will be implemented quicker.” 

Helping the cause are the several events organised on ICT and health. Such as the Women in Data festival and the ICT&Health congress. “There is an under-representation of women in data science and STEM programmes in general, although it has improved in the last years. These kinds of events provide a stage for women to share their work and raise awareness on data science.”