i-SART: An Intelligent Assistant for Safety Analysis in Radiation Therapy

Natalia Silvis-Cividjian, Yijing Zhou, Anastasia Sarchosoglou, Evangelos Pappas

2024

Abstract

Along with surgery and chemotherapy, radiation therapy (RT) is a very effective method to treat cancer. The process is safety-critical, involving complex machines, human operators and software. A proactive hazard analysis to predict what can go wrong in the process is therefore crucial. Failure Modes and Effect Analysis (FMEA) is one of the methods widely used for risk assessment in healthcare. Unfortunately, the available resources and FMEA expertise strongly vary across different RT organizations worldwide. This paper describes i-SART, an interactive web-application that aims to close the gap by bringing together best practices in conducting a sound RT-FMEA. Central is a database that at present contains approximately 420 FMs collected from existing risk assessments and cleaned from ambiguities and duplicates using NLP techniques. Innovative is that the database is designed to grow, due to both user input and generative AI algorithms. This is work in progress. First experiments demonstrated that using machine learning in building i-START is beneficial. However, further efforts will be needed to search for better solutions that do not require human judgment for validation. We expect to release soon a prototype of i-SART that hopefully will contribute to the global implementation and promotion of safe RT practices.

Paper Citation

in Harvard Style

Silvis-Cividjian N., Zhou Y., Sarchosoglou A. and Pappas E. (2024). i-SART: An Intelligent Assistant for Safety Analysis in Radiation Therapy. In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF; ISBN 978-989-758-688-0, SciTePress, pages 420-427. DOI: 10.5220/0012364400003657

in Bibtex Style

@conference{healthinf24,
author={Natalia Silvis-Cividjian and Yijing Zhou and Anastasia Sarchosoglou and Evangelos Pappas},
title={i-SART: An Intelligent Assistant for Safety Analysis in Radiation Therapy},
booktitle={Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF},
year={2024},
pages={420-427},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012364400003657},
isbn={978-989-758-688-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF
TI - i-SART: An Intelligent Assistant for Safety Analysis in Radiation Therapy
SN - 978-989-758-688-0
AU - Silvis-Cividjian N.
AU - Zhou Y.
AU - Sarchosoglou A.
AU - Pappas E.
PY - 2024
SP - 420
EP - 427
DO - 10.5220/0012364400003657
PB - SciTePress