Triage Model using LightGBM by osama zamanTriage Model using LightGBM by osama zaman

Triage Model using LightGBM

osama zaman

osama zaman

Triagegeist

Competition Notebook

Input

Output

Runtime

2m 52s · GPU T4 x2

Language

Python
import pandas as pd import numpy as np import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec import seaborn as sns import warnings warnings.filterwarnings('ignore') from sklearn.preprocessing import LabelEncoder from sklearn.model_selection import StratifiedKFold, cross_val_score from sklearn.metrics import (classification_report, confusion_matrix, f1_score, accuracy_score, cohen_kappa_score) from sklearn.calibration import calibration_curve import lightgbm as lgb import shap

Derived Triage Acuity Distribution

print("=== Derived Triage Acuity Distribution ===") print(train['triage_acuity'].value_counts().sort_index())

Triage Model Results

Submission Details

Submission shape: (20000, 2)
Acuity distribution:
triage_acuity 1 3425 2 1949 3 3399 4 1766 5 9461
Like this project

Posted May 11, 2026

Developed a triage model using Python and LightGBM to predict patient acuity based on clinical data.