Machine learning in diagnostic support in medical emergency departments.

Diagnosing patients in the medical emergency department is complex and this is expected to increase in many countries due to an ageing population. In this study we investigate the feasibility of training machine learning algorithms to assist physicians handling the complex situation in the medical emergency departments. This is expected to reduce diagnostic errors and improve patient logistics and outcome.

Glycemic control in diabetes in three Danish counties.

Background: Hemoglobin A1c (HbA1c) is a proxy measure for glycemic control in diabetes. We investigated the trend for glycemic control in patients from three Danish counties using HbA1c measurements.

Methods: We studied 2454 patients from a population of 807,000 inhabitants for whom routine monitoring of diabetes using HbA1c-DCCT aligned was initiated in 2001.