Conceptual Explanations of ECG Classification using Large Language Models
Article No.: 59, Pages 1 - 3
Abstract
Conceptual-level explanations of ECG signals has been of great interest in order that arrhythmias can be automatically classified and explained. We leverage and evaluate the power of large language models (LLMs), specifically ChatGPT, to generate the main conceptual features extraction code from raw ECG data and perform classification. Thereafter, we use ChatGPT to generate meaningful conceptual level explanations for the outcomes. Results suggest that ChatGPT is able to provide accurate and consistent explanations for ECG classification. In addition to this, the explanations are simple and and meaningful for doctors.
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- Conceptual Explanations of ECG Classification using Large Language Models
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Published In
October 2023
381 pages
ISBN:9798400716492
DOI:10.1145/3639856
Copyright © 2023 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 17 May 2024
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- Demonstration
- Research
- Refereed limited
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AIMLSystems 2023
AIMLSystems 2023: The Third International Conference on Artificial Intelligence and Machine Learning Systems
October 25 - 28, 2023
Bangalore, India
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