The study for dispatch decision of medical emergency resources with real-time spatial analysis
暂无分享,去创建一个
Yen-Jen Oyang | Horng-Twu Liaw | Chih-Hong Sun | Wei-Zen Sun | Jui-Hung Kao | Po-Huan Hsiao | Shin-Wen Chang | H. Liaw | J. Kao | Chih-Hong Sun | Wei-Zen Sun | Po-Huan Hsiao | Shin-Wen Chang | Yen-Jen Oyang
[1] D J Roe,et al. Estimating effectiveness of cardiac arrest interventions: a logistic regression survival model. , 1997, Circulation.
[2] Theodore J Iwashyna,et al. Small Area Variations in Out-of-Hospital Cardiac Arrest: Does the Neighborhood Matter? , 2010, Annals of Internal Medicine.
[3] Yen-Jen Oyang,et al. Data classification with a relaxed model of variable kernel density estimation , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..
[4] Richard C. Sadler,et al. Bystander Cardiopulmonary Resuscitation Is Clustered and Associated With Neighborhood Socioeconomic Characteristics: A Geospatial Analysis of Kent County, Michigan , 2017, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.
[5] L. Anselin. Local Indicators of Spatial Association—LISA , 2010 .
[6] Stefano Di Bartolomeo,et al. Emergency medical service treated out-of-hospital cardiac arrest: Identification of weak links in the chain-of-survival through an epidemiological study , 2016, European journal of cardiovascular nursing : journal of the Working Group on Cardiovascular Nursing of the European Society of Cardiology.
[7] P. Diggle. Applied Spatial Statistics for Public Health Data , 2005 .
[8] Alain Cariou,et al. The CAHP (Cardiac Arrest Hospital Prognosis) score: a tool for risk stratification after out-of-hospital cardiac arrest. , 2016, European heart journal.
[9] Conor Teljeur,et al. The Effect of Rurality on Out‐of‐Hospital Cardiac Arrest Resuscitation Incidence: An Exploratory Study of a National Registry Utilizing a Categorical Approach , 2019, The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association.
[10] Sang Do Shin,et al. Dispatcher-assisted bystander cardiopulmonary resuscitation in rural and urban areas and survival outcomes after out-of-hospital cardiac arrest. , 2018, Resuscitation.
[11] Tijs Neutens,et al. A commuter-based two-step floating catchment area method for measuring spatial accessibility of daycare centers. , 2015, Health & place.
[12] J. Bakker,et al. Persistent peripheral and microcirculatory perfusion alterations after out-of-hospital cardiac arrest are associated with poor survival* , 2012, Critical care medicine.
[13] J. Claridge,et al. Trauma system regionalization improves mortality in patients requiring trauma laparotomy , 2017, The journal of trauma and acute care surgery.
[14] Bruno Hansen,et al. FirstAED emergency dispatch, global positioning of community first responders with distinct roles - a solution to reduce the response times and ensuring an AED to early defibrillation in the rural area Langeland , 2016, Int. J. Netw. Virtual Organisations.
[15] P. J. Green,et al. Density Estimation for Statistics and Data Analysis , 1987 .
[16] Hanno L. Tan,et al. Abstract 246: Reduced Prehospital Survival Rate After Out-of-Hospital Cardiac Arrest in Patients with Diabetes Mellitus Type 2: A Prospective Community-Based Study , 2014 .
[17] Ajit Pratap Singh,et al. Quantifying Accessibility to Health Care Using Two-step Floating Catchment Area Method (2SFCA): A Case Study in Rajasthan , 2016 .
[18] Doron Aronson,et al. Primary percutaneous coronary intervention after out-of-hospital cardiac arrest: patients and outcomes. , 2007, The Israel Medical Association journal : IMAJ.
[19] Nadine Schuurman,et al. Development of a model to quantify the accessibility of a Canadian trauma system. , 2017, CJEM.
[20] Elizabeth Sinz,et al. 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science , 2010 .
[21] Pemetaan Jumlah Balita,et al. Spatial Scan Statistic , 2014, Encyclopedia of Social Network Analysis and Mining.
[22] Bernard W. Silverman,et al. Density Estimation for Statistics and Data Analysis , 1987 .
[23] Fahui Wang,et al. Measures of Spatial Accessibility to Health Care in a GIS Environment: Synthesis and a Case Study in the Chicago Region , 2003, Environment and planning. B, Planning & design.
[24] Yen-Jen Oyang,et al. Data classification with radial basis function networks based on a novel kernel density estimation algorithm , 2005, IEEE Transactions on Neural Networks.
[25] Mei-Po Kwan,et al. Predicting demand for 311 non-emergency municipal services: An adaptive space-time kernel approach , 2017 .
[26] Hyo Jung Lee,et al. Positive correlation between regional emergency medical resources and mortality in severely injured patients: results from the Korean National Hospital Discharge In-depth Survey. , 2017, CJEM.
[27] Elisabeth Dowling Root,et al. A tale of two cities: the role of neighborhood socioeconomic status in spatial clustering of bystander CPR in Austin and Houston. , 2013, Resuscitation.
[28] Comilla Sasson,et al. Multiple cluster analysis for the identification of high-risk census tracts for out-of-hospital cardiac arrest (OHCA) in Denver, Colorado. , 2014, Resuscitation.
[29] L. Waller,et al. Applied Spatial Statistics for Public Health Data: Waller/Applied Spatial Statistics , 2004 .
[30] Maysam F. Abbod,et al. Big data analysis of emergency medical service applied to determine the survival rate effective factors and predict the ambulance time variables , 2017 .
[31] Khalid Alnemer,et al. Ambulance response time to cardiac emergencies in Riyadh , 2016 .
[32] Masoud Swalehe,et al. Dynamic Ambulance Deployment to Reduce Ambulance Response Times Using Geographic Information Systems: A Case Study of Odunpazari District of Eskisehir Province, Turkey☆ , 2016 .
[33] Benjamin S. Abella,et al. Increasing cardiopulmonary resuscitation provision in communities with low bystander cardiopulmonary resuscitation rates: a science advisory from the American Heart Association for healthcare providers, policymakers, public health departments, and community leaders. , 2013, Circulation.
[34] Yasunori Sato,et al. Impact of geographic accessibility on utilization of the annual health check-ups by income level in Japan: A multilevel analysis , 2017, PloS one.
[35] Yan-Ren Lin,et al. Characteristics and Risk Factors of Out-of-Hospital Cardiac Arrest Within 72 Hours After Discharge , 2015, The American journal of the medical sciences.
[36] Arthur L. Kellermann,et al. Predictors of Survival From Out-of-Hospital Cardiac Arrest A Systematic Review and Meta-Analysis , 2013 .