Future vision: learning from all data
Imagine that a kind of intelligent system has even more data at its disposal from which to learn. Not only from scans, but also genetic data, blood tests or, for example, data from wearables that monitor your heart function for a day. Imagine that a system of this kind also has the values from other patients at its disposal, with which to make comparisons. This is the vision of the future that Wiro Niessen, a qualified physicist, is endeavouring to work towards.
The Professor of Biomedical Image Analysis and Machine Learning at TU Delft and Erasmus MC can picture it all: ‘We’re creating Diagnostic Competence Centres that will play a key role in disease prevention, detection, diagnosis and prognosis. In them, we will bring together different types of data and apply AI techniques to learn how to use all that information to improve diagnosis and prognosis.
‘For example, we can develop an AI algorithm using data from prostate cancer patients in different hospitals. Based on those data, we can then learn the relationship between the diagnostic data and the outcome for the patient; this will enable us to develop a system able to look at each new patient and estimate what type of tumour they have and what the prognosis and expected response to therapy will be.’
“Directorate-general for data management”
According to Niessen, there are large amounts of data that have been hardly used at all until now. ‘You do a scan, decide on a conclusion for this patient and often that’s as far as it goes. The challenge will be to develop an infrastructure that enables us to reuse data to develop algorithms. This will not require all of the data from all hospitals to be included in a single system, but if all hospitals store their data in a standardised way, algorithms will be able to make sense of it. What we really need is a “directorate-general for data management” like the one we have for water, we sometimes joke. By way of example, we’re currently working on a nationwide data portal as part of our response to Covid-19.’
Leiden <=> Delft <=> Erasmus
Niessen forms the link between scientists from TU Delft and those at Erasmus MC. ‘Many of my Master’s students from Delft, a lot of them engineers or AI specialists, do internships at the Erasmus MC. Students from various faculties at Delft − Applied Sciences, EEMCS, Biomedical Engineering − are very interested in medical issues.’