Electronic patient‑reported outcomes and machine learning in predicting immune‑related adverse events of immune checkpoint inhibitor therapies
Deep learning systems have widely presented promising results in cancer diagnostics and for Kaiku Health, machine learning (ML) based approaches are not anything new. Previously, Oulu University Hospital (OYS) and Kaiku Health have shown that it is possible to predict both symptom and adverse event onset and continuation in patients receiving immune checkpoint inhibitor (ICI) therapies. In a previous study, the company investigated whether machine learning could be used to predict the treatment response, or more specifically objective response rate (ORR) of ICI-treated patients, based on clinical and patient-reported data.
#platform
#ml