In a children’s house in Munich there are young patients who are not able to breath independently. Meanwhile, due to their physical problems, they often need medication and special cares, which – in combination- can lead to side-effects. The problem becomes even more serious as these children are not able to easily communicate, which makes it difficult for caregivers and doctors to interpret e.g. restlessness of patients.
Microsoft, Trivadis, and other partners have started to support the children house by offering their technical expertise.
At Trivadis, we predominantly work on the Data and AI stream, essentially collecting real-time data from ventilators and ECG medical devices and other data sources, such as nutrition and medication databases. The collected data are then processed using analytic and AI methods to better understand the condition of the patients with the goal of reducing their medication and stress.
In this talk, I present the intelligent solution of our team at Trivadis, ranging from data collection to machine learning and data visualization. The impact of our intermediate results, lessons learned, and future directions will be discussed as well.
Dr. Maryam Bagher Oskouei – Trivadis GmbH
Dr. Maryam Bagher Oskouei currently works as a Data Scientist at Trivadis Germany GmbH, Düsseldorf. She works on various projects, including the one, that is presented in this talk. Her responsibilities at Trivadis also include providing internal and external training in data science and big data analytics.
Before Trivadis, she worked at the Max Planck Institute for Biological Cybernetics as a postdoctoral fellow. Her focus was on data analysis, modelling, planning and execution of biological experiments focusing on brain energy metabolism.
Prior to this, she worked as a research fellow at the California Institute of Technology (Caltech) on Gene regulatory networks projects. She completed her PhD in computer science in the Artificial Intelligence Laboratory at the University of Otago.