Doctors often have to make important decisions before all information is available. At the same time, routinely collected medical data may already contain valuable signals that are easy to overlook. This research shows how artificial intelligence (AI) can help make better use of these early signals.
In the clinical laboratory, AI recognized patterns in routine blood test results linked to inherited blood disorders. This helps identify patients who may benefit from further testing.
In the emergency department, AI estimated the risk of appendicitis in patients with acute abdominal pain using information available during the first assessment. The approach also worked well in other Dutch hospitals and made doctors’ assessments more consistent and accurate.
These results show that AI can make better use of information already available in routine care. For patients, this may mean an earlier diagnosis, more targeted testing, and a lower risk of unnecessary tests or a missed diagnosis.
About the PhD candidate
Anoeska Schipper (1987) studied Communication Science at the University of Amsterdam and completed her Research Master cum laude in 2012. After graduating, she worked at Deloitte in forensic IT, focusing on data analytics and artificial intelligence. In 2021, she became a Data Scientist at Jeroen Bosch Hospital. Since 2022, she has conducted PhD research at Radboud university medical center on AI for early diagnostic decision-making.