Dr. Xuehuan He

Dr. Xuehuan He

PostDoc Associate at the University of Pittsburgh

Publications

Please visit my Google Scholar profile.

The full-text of my articles are accessible or can be accessed on request on my Researchgate Profile

Journal Publications

  1. Kim, T.; Tjahjadi, N.S.; He, X.; van Herwaarden, J.; Patel, H.J.; Burris, N.S.; Figueroa, C.A. Three-Dimensional Characterization of Aortic Root Motion by Vascular Deformation Mapping. J. Clin. Med. 2023, 12, 4471.

  2. He, X., & Lu, J. (2022). On strain-based rupture criterion for ascending aortic aneurysm: The role of fiber waviness. Acta biomaterialia, 149, 51-59.

  3. He, X., & Lu, J. (2022). Modeling planar response of vascular tissues using quadratic functions of effective strain. International Journal for Numerical Methods in Biomedical Engineering, e3653.

  4. He, X., & Lu, J. (2022). Explicit consideration of fiber recruitment in vascular constitutive formulation using beta functions. Journal of the Mechanics and Physics of Solids, 163, 104837.

  5. He, X., Auricchio, F., Morganti, S., & Lu, J. (2021). Uniaxial properties of ascending aortic aneurysms in light of effective stretch. Acta Biomaterialia, 136, 306-313.

  6. He, X., Avril, S., & Lu, J. (2021). Prediction of local strength of ascending thoracic aortic aneurysms. Journal of the Mechanical Behavior of Biomedical Materials, 115, 104284.

  7. He, X., Avril, S., & Lu, J. (2021). Estimating aortic thoracic aneurysm rupture risk using tension–strain data in physiological pressure range: an in vitro study. Biomechanics and Modeling in Mechanobiology, 20(2), 683-699.

  8. Lu, J., & He, X. (2021). Incorporating fiber recruitment in hyperelastic modeling of vascular tissues by means of kinematic average. Biomech Model Mechanobiol, 20(5), 1833-1850.

  9. He, X., Avril, S., & Lu, J. (2019). Machine learning prediction of tissue Strength and local Rupture risk in Ascending thoracic Aortic Aneurysms. Molecular & Cellular Biomechanics, 16(S2): 50 -52.

  10. He, X., Bai, J., & Zhou, D. (2019). Numerical Evaluation of the Performance Efficiency of Small-Caliber Colonoscopes in Reducing Patient Pain during a Colonoscopy: Influence of Gender. International Journal of Pharma Medicine and Biological Sciences, 8(2), 28-33.

  11. Zhou, D., & He, X. (2019). Numerical evaluation of the efficacy of small-caliber colonoscopes in reducing patient pain during a colonoscopy. Computer methods in biomechanics and biomedical engineering, 22(1), 38-46.

Conference Presentations

  1. He, X. , & Lu, J. Modelling Collagen fiber recruitment in aortic tissue using kinematic average method, Poster session presented at the Virtual Summer Biomechanics, Bioengineering, and Biotransport Conference, June 14 – 18, 2021.

  2. He, X. , & Lu, J. Machine-learning prediction of aortic thoracic aneurysm tissue rupture, Poster session presented at the society of engineering science (SES) virtual technical meeting, September 29 – October 1, 2020.

  3. He, X., Avril, S., & Lu, J. Machine learning prediction of Tissue strength and local Rupture risk in Ascending thoracic Aortic Aneurysms. Oral session presented at the International Conference on Biomechanics and Medical Engineering, San Diego, CA, September 20-23, 2019.

  4. He, X., Ferrara, A., Luo, YM., Auricchio, F. & Lu, J., Machine Learning Prediction of Rupture Strength of Ascending Aortic Aneurysm Tissue. Oral session presented at the Summer Biomechanics, Bioengineering, and Biotransport Conference, Seven Springs, PA, June 25 – 28, 2019.