#8413. Real-time frequency-independent single-Lead and single-beat myocardial infarction detection

September 2026publication date
Proposal available till 30-05-2025
4 total number of authors per manuscript4500 $

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Journal’s subject area:
Medicine (miscellaneous);
Artificial Intelligence;
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Abstract:
This study applies a deep LSTM network for real-time frequency-independent detection of myocardial infarcts. The network is trained and tested using the PTB-XL database. The is done over distinct datasets, collected under different conditions and from different patients, for a more realistic measure of the performance. The model achieves stable performance metrics over the frequency range of 202 Hz to 2.8 kHz.
Keywords:
Cardiovascular disease; Electrocardiograms; Frequency Independence; Long Short-Term Memory Neural Network; Myocardial infarction; Real-time processing

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