| Autor: |
Cerrito, P B, Koenig, S C, VanHimbergen, D J, Jaber, S F, Ewert, D L, Spence, P A |
| Zdroj: |
European Journal of Cardio-Thoracic Surgery; July 1999, Vol. 16 Issue: 1 p88-93, 6p |
| Abstrakt: |
The intra-operative assessment of the quality of anastomosis in minimally invasive coronary artery bypass surgery (CABG) is critical. Recent investigations demonstrated that flow probes used intra-operatively to assess anastomotic errors may give the surgeon a false sense of confidence as only severely stenotic anastomoses (>90%) could be reliably detected. We developed a neural network system using graft flow data and assessed its potential to improve anastomotic error detection. |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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