The Knowledge Discovery in Healthcare Data (KDH) workshop series was established in 2016 to present AI research efforts to solve pressing problems in healthcare. The workshop series aims to bring together clinical and AI researchers to foster collaboration. This year, the workshop will be held in conjunction with ECAI 2020, in Santiago de Compostela, Spain.
The focus of the workshop is on learning healthcare systems. The notion of the learning healthcare system has been put forward to denote the translation of routinely collected data into knowledge that drives the continual improvement of medical care. This notion has been described in many forms, but each follows a similar cycle of assembling, analyzing and interpreting data from multiple sources (clinical records, guidelines, patient-provided data, sensor data, omics data), followed by feeding the acquired knowledge back into clinical practice. This framework aims to provide personalised recommendations and decision support tools to aid both patients and care providers, to improve outcomes and personalise care. Learning healthcare systems also help to extend the range of actions possible in response to patient monitoring data, for example, alerting patients or automatically adjusting insulin doses when blood glucose levels are predicted to go out of range.
A highlight of KDH 2020 will be the second Blood Glucose Level Prediction (BGLP) Challenge. The first BGLP Challenge was held as part of KDH 2018 at IJCAI-ECAI in Stockholm, Sweden. Blood glucose level prediction is a challenging task for AI researchers with the potential to improve the health and wellbeing of people with diabetes. In the BGLP Challenge, researchers will come together to compare the efficacy of different prediction approaches on a standard set of real patient data.