Dataset: Classification Of Coronary Artery Disease

About this Dataset

Classification Of Coronary Artery Disease

The Z-Alizadeh Sani dataset is one of the most common datasets used in machine learning for automatic CAD detection. This dataset contains 303 samples (216 CAD patients and 87 normal) with 55 features. The main features of this dataset are four categories: (1) Demographic, (2) symptoms and examination, (3) electrocardiogram, and (4) laboratory and echo features.

The main advantage of this dataset is its completeness. There are no missing values or outliers in this dataset
This dataset is publicly available in the UCI Machine Learning repository for researchers📚

Features of Z-Alizadeh Sani dataset

Demographic:

Age 30–86
Weight 48–120
Sex Male, female
BMI (body mass index Kg/m2) 18–41
DM (Diabetes Mellitus) Yes, no
HTN (hyper tension) Yes, no
Current smoker Yes, no
Ex-Smoker Yes, no
FH (family history) Yes, no
Obesity Yes if MBI > 25, no otherwise
CRF (chronic renal failure) Yes, no
CVA (Cerebrovascular Accident) Yes, no
Airway disease Yes, no
Thyroid Disease Yes, no
CHF (congestive heart failure) Yes, no
DLP (Dyslipidemia) Yes, no

Symptom and examination :

BP (blood pressure: mmHg) 90–190
PR (pulse rate) (ppm) 50–110
Edema Yes, no
Weak peripheral pulse Yes, no
Lung rales Yes, no
Systolic murmur Yes, no
Diastolic murmur Yes, no
Typical Chest Pain Yes, no
Dyspnea Yes, no
Function class 1, 2, 3, 4
Atypical Yes, no
Nonanginal CP Yes, no
Exertional CP (Exertional Chest Pain) Yes, no
Low Th Ang (low Threshold angina) Yes, no

ECG:

Rhythm Sin, AF
Q Wave Yes, no
ST Elevation Yes, no
ST Depression Yes, no
T inversion Yes, no
LVH (left ventricular hypertrophy) Yes, no
Poor R progression (poor R wave progression) Yes, no

Laboratory and echo:

FBS (fasting blood sugar) (mg/dl) 62–400
Cr (creatine) (mg/dl) 0.5–2.2
TG (triglyceride) (mg/dl) 37–1050
LDL (low density lipoprotein) (mg/dl) 18–232
HDL (high density lipoprotein) (mg/dl) 15–111
BUN (blood urea nitrogen) (mg/dl) 6–52
ESR (erythrocyte sedimentation rate) (mm/h) 1–90
HB (hemoglobin) (g/dl) 8.9–17.6
K (potassium) (mEq/lit) 3.0–6.6
Na (sodium) (mEq/lit) 128–156
WBC (white blood cell) (cells/ml) 3700–18,000
Lymph (Lymphocyte) (%) 7–60
Neut (neutrophil) (%) 32–89
PLT (platelet) (1000/ml) 25–742
EF (ejection fraction) (%) 15–60
Region with RWMA (regional wall motion abnormality) 0, 1, 2, 3, 4
VHD (valvular heart disease) Normal, mild, moderate, severe

Tables

Cad

@kaggle.saeedeheydarian_classification_of_coronary_artery_disease.cad

46.75 KB
303 rows
55 columns


CREATE TABLE cad (
  "age" BIGINT,
  "weight" BIGINT,
  "length" BIGINT,
  "sex" VARCHAR,
  "bmi" DOUBLE,
  "dm" BIGINT,
  "htn" BIGINT,
  "current_smoker" BIGINT,
  "ex_smoker" BIGINT,
  "fh" BIGINT,
  "obesity" VARCHAR,
  "crf" VARCHAR,
  "cva" VARCHAR,
  "airway_disease" VARCHAR,
  "thyroid_disease" VARCHAR,
  "chf" VARCHAR,
  "dlp" VARCHAR,
  "bp" BIGINT,
  "pr" BIGINT,
  "edema" BIGINT,
  "weak_peripheral_pulse" VARCHAR,
  "lung_rales" VARCHAR,
  "systolic_murmur" VARCHAR,
  "diastolic_murmur" VARCHAR,
  "typical_chest_pain" BIGINT,
  "dyspnea" VARCHAR,
  "function_class" BIGINT,
  "atypical" VARCHAR,
  "nonanginal" VARCHAR,
  "exertional_cp" VARCHAR,
  "lowth_ang" VARCHAR,
  "q_wave" BIGINT,
  "st_elevation" BIGINT,
  "st_depression" BIGINT,
  "tinversion" BIGINT,
  "lvh" VARCHAR,
  "poor_r_progression" VARCHAR,
  "fbs" BIGINT,
  "cr" DOUBLE,
  "tg" BIGINT,
  "ldl" BIGINT,
  "hdl" DOUBLE,
  "bun" BIGINT,
  "esr" BIGINT,
  "hb" DOUBLE,
  "k" DOUBLE,
  "na" BIGINT,
  "wbc" BIGINT,
  "lymph" BIGINT,
  "neut" BIGINT,
  "plt" BIGINT,
  "ef_tte" BIGINT,
  "region_rwma" BIGINT,
  "vhd" VARCHAR,
  "cath" VARCHAR
);