Article Versions Notes

Chiang P-Y, Chao PC-P, Tu T-Y, Kao Y-H, Yang C-Y, Tarng D-C, Wey C-L. Machine Learning Classification for Assessing the Degree of Stenosis and Blood Flow Volume at Arteriovenous Fistulas of Hemodialysis Patients Using a New Photoplethysmography Sensor Device. Sensors. 2019; 19(15):3422. https://doi.org/10.3390/s19153422

Chiang, Pei-Yu, Paul C. -P. Chao, Tse-Yi Tu, Yung-Hua Kao, Chih-Yu Yang, Der-Cherng Tarng, and Chin-Long Wey. 2019. "Machine Learning Classification for Assessing the Degree of Stenosis and Blood Flow Volume at Arteriovenous Fistulas of Hemodialysis Patients Using a New Photoplethysmography Sensor Device" Sensors 19, no. 15: 3422. https://doi.org/10.3390/s19153422

Chiang, P.-Y., Chao, P. C.-P., Tu, T.-Y., Kao, Y.-H., Yang, C.-Y., Tarng, D.-C., & Wey, C.-L. (2019). Machine Learning Classification for Assessing the Degree of Stenosis and Blood Flow Volume at Arteriovenous Fistulas of Hemodialysis Patients Using a New Photoplethysmography Sensor Device. Sensors, 19(15), 3422. https://doi.org/10.3390/s19153422