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This project uses patients' surgery data to derive/design the "most effective model" that will predict the survival of patients (in days) after undergoing a particular type of liver operation. Code was built in R.

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Benjamin-compute/Surgical-Unit

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Surgical-Unit (using R)

A hospital surgery unit was interested in predicting survival in patients undergoing a particular type of liver operation. A random selection of 108 patients was available for analysis. For each patient record, the following information was extracted from the pre-operation evaluation:

  blood:    Blood clotting score

  prog:     Prognostic index

  enzyme:   Enzyme function test score

  liver:    Liver function test score

  age:      Age in years

  gender:   I(person is female) i.e. 0 = male, 1=female

  a.mod:    I(person is a moderate alcohol user) i.e. 0=none, 1 = moderate, 0 = heavy

  a.heavy:  I(person is a heavy alcohol user) i.e. 0=none, 0=moderate, 1=heavy

A follow-up study ascertained the response variable -"survival time", which refers to the amount of time the person survived after the surgery.

The dataset available for this analysis is for the first 54 patients.

The GOAL of this project is to select the best model through the Modeling Building Process.

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This project uses patients' surgery data to derive/design the "most effective model" that will predict the survival of patients (in days) after undergoing a particular type of liver operation. Code was built in R.

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