Othman, G.B.; Ynineb, A.R.; Yumuk, E.; Farbakhsh, H.; Muresan, C.; Birs, I.R.; De Raeve, A.; Copot, C.; Ionescu, C.M.; Copot, D.
Artificial Intelligence-Driven Prognosis of Respiratory Mechanics: Forecasting Tissue Hysteresivity Using Long Short-Term Memory and Continuous Sensor Data. Sensors 2024, 24, 5544.
https://doi.org/10.3390/s24175544
AMA Style
Othman GB, Ynineb AR, Yumuk E, Farbakhsh H, Muresan C, Birs IR, De Raeve A, Copot C, Ionescu CM, Copot D.
Artificial Intelligence-Driven Prognosis of Respiratory Mechanics: Forecasting Tissue Hysteresivity Using Long Short-Term Memory and Continuous Sensor Data. Sensors. 2024; 24(17):5544.
https://doi.org/10.3390/s24175544
Chicago/Turabian Style
Othman, Ghada Ben, Amani R. Ynineb, Erhan Yumuk, Hamed Farbakhsh, Cristina Muresan, Isabela Roxana Birs, Alexandra De Raeve, Cosmin Copot, Clara M. Ionescu, and Dana Copot.
2024. "Artificial Intelligence-Driven Prognosis of Respiratory Mechanics: Forecasting Tissue Hysteresivity Using Long Short-Term Memory and Continuous Sensor Data" Sensors 24, no. 17: 5544.
https://doi.org/10.3390/s24175544
APA Style
Othman, G. B., Ynineb, A. R., Yumuk, E., Farbakhsh, H., Muresan, C., Birs, I. R., De Raeve, A., Copot, C., Ionescu, C. M., & Copot, D.
(2024). Artificial Intelligence-Driven Prognosis of Respiratory Mechanics: Forecasting Tissue Hysteresivity Using Long Short-Term Memory and Continuous Sensor Data. Sensors, 24(17), 5544.
https://doi.org/10.3390/s24175544
