In-Depth Analysis of Recall Initiators of Medical Devices with a Machine Learning-Natural Language Processing Tool

Yang Hu, Pezhman Ghadimi

2024

Abstract

Persistent quality problems with medical devices and the associated recall present potential health risks to patients and users, bringing extra costs to manufacturers and disturbances to the entire supply chain (SC). Recall initiator identification and assessment are the preliminary steps to prevent medical device recall. Conventional analysis tools are inappropriate for processing massive and multi-formatted data comprehensively to meet the higher expectations of delicacy management with the increasing overall data volume and textual data format. To address these problems, this study presents a big data analytics-based Machine learning (ML) – Natural language Processing (NLP) tool to identify, assess and analyse the medical device recall initiators based on the FDA ‘Medical Device Recalls’ database from 2018 to 2024, inclusive. Results suggest that the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm can present each single recall initiator in a specific manner, therefore helping practitioners to identify the recall reasons, comprehensively. This is followed by text similarity-based textual classification to assist practitioners in controlling the group size of recall initiators and provide managerial insights from the operational to the tactical and strategic levels. More proactive practices to prevent medical device recalls are expected in the future.

Paper Citation

in Harvard Style

Hu Y. and Ghadimi P. (2024). In-Depth Analysis of Recall Initiators of Medical Devices with a Machine Learning-Natural Language Processing Tool. In Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-717-7, SciTePress, pages 387-394. DOI: 10.5220/0012900600003822

in Bibtex Style

@conference{icinco24,
author={Yang Hu and Pezhman Ghadimi},
title={In-Depth Analysis of Recall Initiators of Medical Devices with a Machine Learning-Natural Language Processing Tool},
booktitle={Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2024},
pages={387-394},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012900600003822},
isbn={978-989-758-717-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - In-Depth Analysis of Recall Initiators of Medical Devices with a Machine Learning-Natural Language Processing Tool
SN - 978-989-758-717-7
AU - Hu Y.
AU - Ghadimi P.
PY - 2024
SP - 387
EP - 394
DO - 10.5220/0012900600003822
PB - SciTePress