Metadata-Version: 2.1
Name: missedSampleLib
Version: 0.0.3
Summary: missedSampleLib
Home-page: UNKNOWN
Author: Jordi Tortosa Carreres
Author-email: tortosacarreresjordi@gmail.com
License: UNKNOWN
Keywords: python,missedSampleLib,misidentified samples
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
License-File: license

This repository contains the Python-based machine learning model developed as part of the study titled:
"Development and Validation of a CDS-Based Machine Learning Model for Accurate Detection of Misidentified Samples in Hospitalized Patients".
The model, built using the XGBoost algorithm, was trained on real-world clinical data from hospitalized patients to detect sample misidentification errors (MIS), including:
•	MIS cases: confirmed errors (25%) and randomly simulated sample reordering (25%)
•	Properly identified control samples (50%)
This package was specifically designed for integration into a Clinical Decision Support System (CDS) to automate the detection of analytical inconsistencies and enhance patient safety in routine clinical workflows.
Repository contents:
•	Trained model script (.py)
•	Brief documentation for implementation
This file is part of the technical supplementary material associated with the manuscript, and is provided to support transparency, reproducibility, and practical deployment.


