The objective of this Bioengineering Research Partnership, established in October 2003, is to develop and evaluate advanced ICU patient monitoring and decision support systems that will improve the efficiency, accuracy, and timeliness of clinical decision-making in critical care. The partnership combines the resources of a powerful interdisciplinary team from academia (MIT), industry (Philips Medical Systems and Philips Research North America), and clinical medicine (Beth Israel Deaconess Medical Center). During the initial funding period of this BRP substantial progress has been achieved, including the development of a massive new research database from more than 30,000 ICU patients (the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) II database) and a number of promising advanced monitoring concepts and algorithms. Our initial work has substantiated the hypothesis that sophisticated analysis of the rich multi-parameter data gathered from ICU patients can illuminate their changing pathophysiologic state, and can even provide alerts of impending changes in state. The major goals for the second phase of this BRP are to develop and demonstrate the effectiveness of advanced monitoring concepts and algorithms in laboratory studies utilizing the resources of MIMIC II, and then to carry successful concepts forward into clinical tests in the ICUs of Beth Israel Deaconess Medical Center (BIDMC) and elsewhere with the collaboration of our clinical and industrial partners. We also will enhance the value and availability of the MIMIC II database by adding new adult and neonatal data, designing and improving sophisticated data mining and signal processing tools, and freely distributing to the research community the database and its associated exploration tools via PhysioNet (www.physiionet.org).
The objective of this Bioengineering Research Partnership, established in October 2003, is to develop and evaluate advanced ICU patient monitoring and decision support systems that will improve the efficiency, accuracy, and timeliness of clinical decision-making in critical care.
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