This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. To support the development of next-generation intelligent patient monitoring systems for ICU patient care, we are developing a massive temporal medical database of unprecedented size from ICU patients (MIMIC-II). Using modern networking and database technologies, we are archiving patient records that include several channels of medical parameters (heart rate, blood pressures), waveforms (ECG, blood pressures), and all the available data from clinical information systems (fluid balance, medications, lab results, nurse text notes). We have hitherto collected over 120 gigabytes of data, including nearly 700 individual patient records. A patient record may span from a few hours to 200 or more hours; from an ICU admission to a discharge. We are currently creating a user-friendly relational database to allow for simplified searching and indexing of MIMIC-II. We have developed novel temporal query abstractions that will efficiently support a wide variety of queries, as well as data mining and knowledge-discovery research. Using MIMIC-II, we are currently evaluating novel intelligent monitoring algorithms and display frameworks that we have recently developed.
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