Chalumuri, Y.R.; Kimball, J.P.; Mousavi, A.; Zia, J.S.; Rolfes, C.; Parreira, J.D.; Inan, O.T.; Hahn, J.-O.
Classification of Blood Volume Decompensation State via Machine Learning Analysis of Multi-Modal Wearable-Compatible Physiological Signals. Sensors 2022, 22, 1336.
https://doi.org/10.3390/s22041336
AMA Style
Chalumuri YR, Kimball JP, Mousavi A, Zia JS, Rolfes C, Parreira JD, Inan OT, Hahn J-O.
Classification of Blood Volume Decompensation State via Machine Learning Analysis of Multi-Modal Wearable-Compatible Physiological Signals. Sensors. 2022; 22(4):1336.
https://doi.org/10.3390/s22041336
Chicago/Turabian Style
Chalumuri, Yekanth Ram, Jacob P. Kimball, Azin Mousavi, Jonathan S. Zia, Christopher Rolfes, Jesse D. Parreira, Omer T. Inan, and Jin-Oh Hahn.
2022. "Classification of Blood Volume Decompensation State via Machine Learning Analysis of Multi-Modal Wearable-Compatible Physiological Signals" Sensors 22, no. 4: 1336.
https://doi.org/10.3390/s22041336
APA Style
Chalumuri, Y. R., Kimball, J. P., Mousavi, A., Zia, J. S., Rolfes, C., Parreira, J. D., Inan, O. T., & Hahn, J.-O.
(2022). Classification of Blood Volume Decompensation State via Machine Learning Analysis of Multi-Modal Wearable-Compatible Physiological Signals. Sensors, 22(4), 1336.
https://doi.org/10.3390/s22041336
