In order to advance machine learning and artificial intelligence in healthcare, Royal Philips, a provider of health technology, today announced a collaboration with MIT’s Institute for Medical Engineering and Science (IMES).
De-identified data from 200,000 critical care patients, including those affected by COVID-19, are included in the revised eICU Collaborative Research Database (eICU-CRD). The creation of solutions that enhance patient care and clinical outcomes will be aided by the larger and more clinically reliable data collection.
The COVID-19 pandemic resulted in a sharp rise in the number of patients in the eICU and critical care settings as well as particular difficulties in the delivery of care. This led Philips and IMES to expand the initial data set, first made public in 2016.
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De-identified and comprehensive clinical data, including vital signs, prescription drug prescriptions, laboratory test results, diagnoses, and severity of disease scores, are contained in the new secure database. Comprehensive information on patient therapies, comorbidities, readmissions, and clinical outcomes is also provided by the dataset.
Researchers from across the world will have access to the data, thanks to researchers at Philips and the Laboratory of Computational Physiology at IMES. This will allow researchers to create cutting-edge algorithms and offer fresh perspectives on critical care.
The Laboratory of Computational Physiology will be the initiative’s academic research center, providing and maintaining access as well as assisting with database education and providing a forum for collaboration. To individuals who have the necessary credentials, have completed human subjects training, and have signed a data usage agreement, the database is available for use in medical research.
