DIAGNOSIS OF RESPIRATORY RHYTHM BASED ON PHYSIOLOGICAL PARAMETERS OF PLETHYSMOGRAPHY USING ARTIFICIAL INTELLIGENCE
DOI:
https://doi.org/10.30888/2663-5712.2024-25-00-058Keywords:
Respiratory rhythm diagnostics, artificial intelligence, photoplethysmography, Long Short-Term Memory (LSTM), heart rate, blood oxygen level (SO2), MAX30102, medical diagnostics, physiological parameters.Abstract
This article discusses the problem of diagnosing respiratory rhythm based on physiological indicators of plethysmography using artificial intelligence. Diseases of the respiratory system are becoming more common, especially after the COVID-19 epidemic. TMetrics
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