Preprocessing and simulation of out of hospital cardiac arrest outcomes data
Out-of-hospital cardiac arrest (OHCA) is a cessation of cardiac mechanical activity that occurs outside of the hospital setting and is confirmed by the absence of signs of circulation. OHCA affects nearly 1000 adult Americans every day, with overall survival rate of 10.4%. Based on previous work in this subject I try to calculate the joint probability distributions of the neurological outcomes of the OHCA outcomes in our records, based on the Event Demographics, Field Care, and Hospital Care. Using Python, I was able to develop an algorithm to calculate various joint probability distributions for the event outcomes from the event demographics, field, and hospital care features.
TABLE OF CONTENTS
ABSTRACT
PROJECT OBJECTIVE
DATA SOURCE
PROJECT CONCLUSIONS
II. PROJECT DEFINITION
III. PROCESS
UTILIZATION OF TRAINED MODEL
THE PREPROCESSING OF THE DATA FOR SIMULATION
THE SIMULATION OF BLOCKS OF DATA
SIMULATION VERIFICATION
IV. CONCLUSIONS
DELIVERABLES
CONCLUSION
FUTURE WORK
V. APPENDIX
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