Help physicians to make the best decision for the treatment of patients with terminal lung cancer
The goal of this project was to give physicians access a prediction model in an easy-to-use interface accessible from their own clinical systems.
We developed a prediction model for terminal stage lung cancer patients that will help to decide whether or not to undergo Prophylactic Cranial Irradiation (PCI). PCI treatment reduces the effects of metastases in the brain in the long term, but has many severe side effects on the short term and no effect on survival time. Therefore, it is important for patients and doctors to determine which patients will live long enough to benefit from the long term benefits of this treatment.
We developed an easy-to-use interface for this model accessible from within the electronic health record system. To further reduce the threshold for usage, we made it possible to automatically feed the data into the underlying data warehouse.
When we have funds to scale-up of this approach, we intend to apply the PHT for the automatic filling of data from multiple hospitals.
We are currently analysing the study results.
Lowering the threshold for usage is key to the implementation of AI in the clinic.
We are using this technology in other projects for example in project “PROSPECT”.
Prof. Dirk de Ruysscher