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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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