PhysioNet, established in 1999 as the NIH-sponsored Research Resource for Complex Physiologic Signals, has attained a preeminent status among biomedical data and software resources. Its data archive, PhysioBank, was the first, and remains the world's largest, most comprehensive and widely used repository of time-varying physiologic signals. PhysioToolkit, its software collection, supports exploration and quantitative analyses of PhysioBank and similar data with a wide range of well-documented, rigorously tested open-source software that can be run on any platform. PhysioNet's team of researchers leverages results of other funded projects to drive the creation and enrichment of: i) Data collections that provide increasingly comprehensive, multifaceted views of pathophysiology over long time intervals, such as the MIMIC III (Medical Information Mart for Intensive Care) Database of critical care patients; ii) Analytic methods that lead to more timely and accurate diagnoses of major public health problems (such as life-threatening cardiac arrhythmias, infant apneas, fall risk in older individuals and those with neurologic disease, and seizures), and iii) Elucidation of dynamical changes associated with a variety of pathophysiologic processes and aging (such as cardiopulmonary interactions during sleep disordered breathing syndromes); User interfaces, reference materials and services that add value and improve accessibility to PhysioNet's data and software (such as PhysioNetWorks, a virtual laboratory for data sharing). Impact: Cited in The White House Fact Sheet on Big Data Across the Federal Government (March 29, 2012), PhysioNet is a proven enabler and accelerator of innovative research by investigators with a diverse range of interests, working on projects made possible by data that are inaccessible otherwise. The creation and development of PhysioNet were recognized with the 2016 highest honor of the Association for the Advancement of Medical Instrumentation (AAMI). PhysioNet's world- wide, growing community of researchers, clinicians, educators, students, and medical instrument and software developers, retrieve about 380 GB of data per day. By providing free access to its unique and wide-ranging data and software collections, PhysioNet is invaluable to studies that currently result in an impressive average of nearly 250 new scholarly articles per month by academic, clinical, and industry-affiliated researchers worldwide. Over the next year we aim to sustain and enhance PhysioNet's impact with new technology and data; and complete the 2019 PhysioNet/Computing in Cardiology Challenge on sepsis.

Public Health Relevance

PhysioNet, the Research Resource for Complex Physiological Signals, maintains the world's largest, most comprehensive and most widely used repository of physiological data and data analysis software, making them freely available to the research community. PhysioNet is a proven enabler and accelerator of innovative biomedical research through its unique role in providing data and other resources that otherwise would be inaccessible.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
3R01GM104987-12S1
Application #
9993811
Study Section
Program Officer
Resat, Haluk
Project Start
2007-09-01
Project End
2020-06-30
Budget Start
2018-07-01
Budget End
2020-06-30
Support Year
12
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Beth Israel Deaconess Medical Center
Department
Type
DUNS #
071723621
City
Boston
State
MA
Country
United States
Zip Code
02215
Zuzarte, Ian; Indic, Premananda; Sternad, Dagmar et al. (2018) Quantifying Movement in Preterm Infants Using Photoplethysmography. Ann Biomed Eng :
Pollard, Tom J; Johnson, Alistair E W; Raffa, Jesse D et al. (2018) The eICU Collaborative Research Database, a freely available multi-center database for critical care research. Sci Data 5:180178
Geovanini, Glaucylara Reis; Wang, Rui; Weng, Jia et al. (2018) Elevations in neutrophils with obstructive sleep apnea: The Multi-Ethnic Study of Atherosclerosis (MESA). Int J Cardiol 257:318-323
Li, Taibo; Matsushima, Minoru; Timpson, Wendy et al. (2018) Epidemiology of patient monitoring alarms in the neonatal intensive care unit. J Perinatol 38:1030-1038
Chang, Joshua; Paydarfar, David (2018) Evolution of extrema features reveals optimal stimuli for biological state transitions. Sci Rep 8:3403
Johnson, Alistair E W; Aboab, Jerome; Raffa, Jesse D et al. (2018) A Comparative Analysis of Sepsis Identification Methods in an Electronic Database. Crit Care Med 46:494-499
Vest, Adriana N; Da Poian, Giulia; Li, Qiao et al. (2018) An open source benchmarked toolbox for cardiovascular waveform and interval analysis. Physiol Meas 39:105004
Costa, Madalena D; Redline, Susan; Davis, Roger B et al. (2018) Heart Rate Fragmentation as a Novel Biomarker of Adverse Cardiovascular Events: The Multi-Ethnic Study of Atherosclerosis. Front Physiol 9:1117
Lehman, Li-Wei H; Mark, Roger G; Nemati, Shamim (2018) A Model-Based Machine Learning Approach to Probing Autonomic Regulation From Nonstationary Vital-Sign Time Series. IEEE J Biomed Health Inform 22:56-66
Clifford, Gari D; Liu, Chengyu; Moody, Benjamin et al. (2017) AF Classification from a Short Single Lead ECG Recording: the PhysioNet/Computing in Cardiology Challenge 2017. Comput Cardiol (2010) 44:

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