Table 2 Symptoms, signs and laboratory investigations in the heart disease dataset.

From: Fine tuned CatBoost machine learning approach for early detection of cardiovascular disease through predictive modeling

Variable

Interpretation

Age

Patient’s Age/year

Sex

Patient’s Gender, Male/Female

Classes

Types of classes in dataset:

(i) Patient with Disease

(ii) Patient without Disease

ChestPainType

Type of chest pain:

(i) TA: Typical Angina

(ii) ATA: Atypical Angina

(iii) NAP: Non-Anginal Pain

(iv) ASY: Asymptomatic

RestingBP

Patient’s Blood Pressure/mmHg

Cholesterol

Patient’s Cholesterol (mg/dl)

FastingBS

Patient’s fasting blood glucose level

(i) glucose > 120 mg/dL = 1

(ii) glucose below 120 mg/dL = 0

RestingECG

(i) Normal

(ii) ST: ST segment and/or T wave abnormality

(iii) LVH: Probable or Definite Left Ventricular Hypertrophy

MaxHR

Maximum Heart Rate, heart beats per minute

ExerciseAngina

Exercise-associated Angina, present/absent

Oldpeak

Measure of ST Depression

ST_Slope

Slope of Peak Exercise

(i) Up: up sloping

(ii) Flat

(iii) Down: down sloping