The 3rd International Workshop on Knowledge Discovery in Healthcare Data

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 collaborative discussions. This year, the workshop will be co-located with IJCAI/ECAI 2018 in Stockholm, Sweden and the focus is on learning healthcare systems. For the first time, this workshop will feature a challenge: The Machine Learning Blood Glucose Level Prediction Challenge.

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 including wearables, omic data, etc.), 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.

This framework also extends 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. 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 Machine Learning Blood Glucose Level Prediction (BGLP) Challenge, researchers will come together to compare the efficacy of different machine learning prediction approaches on a standard set of real patient data.