Optimizing Non-invasive Fractional Flow Reserve Estimation with Machine Learning-Enhanced 1D Hemodynamic Modeling.
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| Title: | Optimizing Non-invasive Fractional Flow Reserve Estimation with Machine Learning-Enhanced 1D Hemodynamic Modeling. |
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| Authors: | Tanade C; Department of Biomedical Engineering, Duke University, 534 Research Dr., Durham, NC, 27705, USA., Mavi JK; Department of Biomedical Engineering, Duke University, 534 Research Dr., Durham, NC, 27705, USA., Ferreira G; Department of Biomedical Engineering, Duke University, 534 Research Dr., Durham, NC, 27705, USA., Schwaller S; Department of Biomedical Engineering, Duke University, 534 Research Dr., Durham, NC, 27705, USA., Randles A; Department of Biomedical Engineering, Duke University, 534 Research Dr., Durham, NC, 27705, USA. amanda.randles@duke.edu. |
| Source: | Cardiovascular engineering and technology [Cardiovasc Eng Technol] 2026 Apr 29. Date of Electronic Publication: 2026 Apr 29. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Country of Publication: United States NLM ID: 101531846 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1869-4098 (Electronic) Linking ISSN: 1869408X NLM ISO Abbreviation: Cardiovasc Eng Technol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1869-4098 |
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| DOI: | 10.1007/s13239-026-00836-y |
