Predicting pneumonia outcomes: Results (using DataRobot API)

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This post is a supplementary material for an assignment. The assignment is part of the Augmented Machine Learning unit for a Specialised Diploma in Data Science for Business. The aim of this project is to classify if patients with Community Acquired Pneumonia (CAP) became better after seeing a doctor or became worse despite seeing a doctor. Previously, EDA (part1, part 2)and feature enginnering was done in R.

Predicting pneumonia outcomes: Modelling via DataRobot API

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This post is a supplementary material for an assignment. The assignment is part of the Augmented Machine Learning unit for a Specialised Diploma in Data Science for Business. The aim of this project is to classify if patients with Community Acquired Pneumonia (CAP) became better after seeing a doctor or became worse despite seeing a doctor. Previously, EDA (part1, part 2)and feature enginnering was done in R.

Predicting pneumonia outcomes: Feature Engineering

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Intro This post is a supplementary material for an assignment. The assignment is part of the Augmented Machine Learning unit for a Specialised Diploma in Data Science for Business. The aim of the assignment is to use DataRobot for predictive modelling. Exploratory data analysis and feature engineering will be done here in R before the data is imported into DataRobot. The aim of this project is to classify if patients with Community Acquired Pneumonia (CAP) became better after seeing a doctor or became worse despite seeing a doctor.

Predicting pneumonia outcomes: EDA part 2

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Intro 9 Lab_ related category Missing Lab values Outlier Lab values High Lab_Hb levels Low Lab_Neu High Lab_Sugar 10 CS_ cultures related category 11 Abx_ antibiotics related category 11i Class of empirical antibiotics given 11ii Antibiotics given Number of antibiotics given 11iii Duration of antibiotics 12 Care_ continuum of care status category replace 99 Admission status Breathing aid 13 V_ vaccine related category Wrap up This post is a supplementary material for an assignment.

Predicting pneumonia outcomes: EDA part 1

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Intro Data dictionary EDA blueprint Outcome Discard the noise 1 Other_ related category 2 Pt_ Patient related category Appropriate patients Case_number Age 3 R_ Radiology related category Effusion and effusion site On chest x-ray ( R_CXR_effusion, R_CXR_effusionSite) On CT chest (R_CT_effusion, R_CT_effusionSite) 4 SS_ Category related to signs and symptoms of CAP 5 Hx_ medical history category HIV details Heart disease 6 Social_ social history category smoking 7 HCAP_ healthcare associated pneumonia category 8 PE_ observations during physical examination category Missing PE_ values Outlier PE_ values Further investigation of outliers To be continued….