APA (7th ed.) Citation

CN, L., CC, W., PC, C., JJ, L., CP, C., HM, L., . . . PY, K. (2026). Interpretable photoplethysmography-based machine-learning model for noninvasive assessment of systolic blood pressure. Frontiers in physiology, 17, 1779262. https://doi.org/10.3389/fphys.2026.1779262

Chicago Style (17th ed.) Citation

CN, Lin, Wang CC, Chao PC, Lin JJ, Chang CP, Lu HM, Lin PW, and Ko PY. "Interpretable Photoplethysmography-based Machine-learning Model for Noninvasive Assessment of Systolic Blood Pressure." Frontiers in Physiology 17 (2026): 1779262. https://doi.org/10.3389/fphys.2026.1779262.

MLA (9th ed.) Citation

CN, Lin, et al. "Interpretable Photoplethysmography-based Machine-learning Model for Noninvasive Assessment of Systolic Blood Pressure." Frontiers in Physiology, vol. 17, 2026, p. 1779262, https://doi.org/10.3389/fphys.2026.1779262.