Corona Predictor

OBJECTIVE -> The goal is to get real-time forecasts and other critical information to front-line health-care workers and public policy makers as the outbreak unfolds.  -> The objective of the Hackathon is to predict the probability of person getting infected by Covid-19.

BRN -> The basic reproduction number (BRN) is the expected number of cases directly generated by one case.  -> A BRN greater than one indicates that the outbreak is self-sustaining,      while a BRN less than one indicates that the number of new cases decreases over time and eventually the outbreak will stop.  ->  PHASE I   - 3.1     PHASE II  - 2.6     PHASE III - 1.9     PHASE IV  - 0.9 (or) 0.5 -> The BRN of SARS decreased from 2.7 to 0.25 after the patients were isolated and the infection started being controlled.

VARIABLES -> PeopleID(Not a ML variable) -> Region(Not a ML variable) -> Gender: Female-0, Male-1 -> Designation(Not a ML variable) -> Name(Not a ML variable) -> Married: YES-1, NO-0 -> Children: INT -> Occupation: Business-0, Cleaner-1, Clerk-2, Driver-3, Farmer-4, Legal-5, Manufacturing-6, Researcher-7, Sales-8 -> Mode_transport: Car-0, Public-1, Walk-2 -> cases/1M: INT -> Deaths/1M: INT -> comorbidity: None-0, Coronary Heart Disease-1, Diabetes-2, Hypertension-3 -> Age: INT -> Coma score: INT -> Pulmonary score: <100-0, <200-1, <300-2, <400-3 -> cardiological pressure: Normal-0, Elevated-1. Stage-01-2, Stage-02-3 -> Diuresis: INT , None -> Platelets: INT -> HBB: INT -> d-dimer: INT -> Heart rate: INT -> HDL cholesterol: INT -> Charlson Index: INT -> Blood Glucose: INT -> Insurance: INT (Maybe variable) -> Salary: INT (Maybe variable) -> FT/month: INT -> Infect_Prob: float(6 decimals)

Try It out



jupyter-notebook, keras, numpy, pandas, python, tensorflow

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