Support vector machines (SVMs) are well-known machine learning algorithms for
classification and regression applications. In the healthcare domain, they have been used …

Wearable activity trackers (WAT) are electronic monitoring devices that enable users to track
and monitor their health-related physical fitness metrics including steps taken, level of …

The SARS-CoV2 virus, which causes COVID-19 (coronavirus disease) has become a
pandemic and has expanded all over the world. Because of increasing number of cases day …

Intensive-care clinicians are presented with large quantities of measurements from multiple
monitoring systems. The limited ability of humans to process complex information hinders …

Recent attempts to achieve fairness in predictive models focus on the balance between
fairness and accuracy. In sensitive applications such as healthcare or criminal justice, this …

Health care is one of the most exciting frontiers in data mining and machine learning.
Successful adoption of electronic health records (EHRs) created an explosion in digital …

Background The broad adoption of electronic health records (EHRs) provides great
opportunities to conduct health care research and solve various clinical problems in …

Deep learning models (aka Deep Neural Networks) have revolutionized many fields
including computer vision, natural language processing, speech recognition, and is being …

which reflects known clinical findings. Differences in prediction accuracy and therefore
machine bias are shown with respect to gender and insurance type for ICU mortality and …

Machine learning for healthcare researchers face challenges to progress and reproducibility
due to a lack of standardized processing frameworks for public datasets. We present MIMIC …