Development of Deep-Learning Models for Real-Time Anaerobic Threshold and Peak VO2 Prediction during Cardiopulmonary Exercise Testing.

Tatsuya WatanabeTakeshi TohyamaMasataka IkedaTakeo FujinoToru HashimotoShouji MatsushimaJunji KishimotoKoji TodakaShintaro KinugawaHiroyuki TsutsuiTomomi Ide

Published in: European journal of preventive cardiology (2023)

Deep-learning models for real-time CPET analysis can accurately identify AT and predict peak VO2. The developed models can be a competent assistant system to assess the patient's condition in real-time, expanding CPET utility.

Keyphrases

deep learning
convolutional neural network
artificial intelligence
wastewater treatment
high intensity
body composition
heavy metals