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thanks to the dataset's extensive collection of variables related to stroke

events.

The Fedesoriano's Stroke Prediction Dataset consists of a diverse set of

records collected from a healthcare facility. It contains anonymized patient
information, including demographic characteristics, lifestyle factors, pre-

existing medical conditions, and various clinical measurements. The dataset

is structured and provided in a CSV format, making it easily accessible for
analysis and model development. Table 2.1 shows data description of the

dataset.

Table 2.1 Data Description of the Fedesoriano’s Stroke Prediction Dataset

Data Description

Id Unique identifier for each patient
gender Gender of the patient (categorical: "Male", "Female", or "Other")

age age: Age of the patient in years (continuous)
hypertension Indicates whether the patient has hypertension (0 - No, 1 - Yes)

Heart_disease Indicates whether the patient has a heart disease (0 - No, 1 - Yes)
Ever_married Indicates the marital status of the patient (categorical: "No" or
"Yes")

Work_type Type of occupation of the patient (categorical: "Private", "Self-
employed", "Govt_job", "children", or "Never_worked")

Residence_type Residence type of the patient (categorical: "Urban" or "Rural")

avg_glucose_level Average glucose level in the patient's blood measured in mg/dL
(continuous)

bmi Body mass index (BMI) of the patient (continuous)

Smoking_status Smoking status of the patient (categorical: "formerly smoked",
"never smoked", "smokes", or "Unknown")

stroke Indicates whether the patient had a stroke or not (0 - No, 1 - Yes)

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