Skip to content
DraconiticResearch
Search Sources API
186,123 studies31 sourcesUpdated 47 min ago
Peer-reviewedCC BYFrontiers in physiology

Dynamic graph vector autoregression for characterizing cardiac electromechanical dynamics during incremental exercise from the joint phase space of electrocardiogram and phonocardiogram

  • Xiaohong Ye1
  • Qiang Lu2
  • Qianyu Lin1
  1. 1Chengyi College, Jimei University , ,
  2. 2School of Science, Jimei University , ,
Read full textPDFCite

Related

  1. Diagnostic Performance of a Deep Learning Model Using Phonocardiogram and Single‐Lead ECG Signals for Detecting Moderate‐or‐Greater Aortic Stenosis: Multicenter External Validation
    Shumpei Saito, Masanobu Ishii, Shimpei Ogawa +21
    Clinical cardiologyPeer-reviewedCC BYFull textCardiovascular medicineEurope PMC
  2. External validation of artificial intelligence-guided electrocardiogram (AI-ECG) in detecting asymptomatic left ventricular dysfunction: A systematic review and meta-analysis
    Jacky Chen, Thomas H Marwick, Cheng Hwee Soh
    American journal of preventive cardiologyPeer-reviewedCC BY-NC-NDFull textGeneral medicineEurope PMC
  3. A multimodal optimisation framework for cardiac electrophysiology model personalisation using computed tomography and 12-lead electrocardiogram: Algorithm development and validation
    Buntheng Ly, Nicolas Cedilnik, Mihaela Pop +5
    JRSM Cardiovascular DiseasePeer-reviewedLicence not statedFull textCardiovascular medicinePMC
  4. Simultaneous evoked CMAP recording and sonography reveal a prolonged electromechanical delay in ALS patients
    Sebastian A. Wölk, Uwe Walter, Johannes Prudlo +2
    Frontiers in NeurologyPeer-reviewedCC BY 4.0Full textNeurologyCrossref
  5. Foundation Model Artificial Intelligence for Electrocardiogram Detection of Rheumatic Mitral Stenosis
    R. Sriram, I. Nenadic, Z. Loring +4
    medRxivPreprintCC BYFull textCardiovascular medicinemedRxiv

Cite

BibTeXRIS
BibTeX
@article{ye2026dynamic,
  title = {{Dynamic graph vector autoregression for characterizing cardiac electromechanical dynamics during incremental exercise from the joint phase space of electrocardiogram and phonocardiogram}},
  author = {Xiaohong Ye and Qiang Lu and Qianyu Lin},
  journal = {Frontiers in physiology},
  year = {2026},
  month = oct,
  url = {https://europepmc.org/article/PMC/PMC13657968},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Dynamic graph vector autoregression for characterizing cardiac electromechanical dynamics during incremental exercise from the joint phase space of electrocardiogram and phonocardiogram
AU  - Xiaohong Ye
AU  - Qiang Lu
AU  - Qianyu Lin
PY  - 2026
DA  - 2026/10/16
JO  - Frontiers in physiology
UR  - https://europepmc.org/article/PMC/PMC13657968
SN  - 1664-042X
ER  -