Optimization of Esophageal Ultrasound under Artificial Fish Swarm Algorithm and Its Adoption in Treatment of Ventricular Septal Defect

Abstract

This work was aimed at exploring the adoption value of the optimized and upgraded esophageal ultrasound in the treatment of patients with ventricular septal defect (VSD) by artificial fish swarm algorithm. A model was built based on artificial fish swarm algorithm. A random ultrasonic optical signal in the database was decomposed several times and sparsity was optimized to complete partial optimization, which was then extended to global optimization. A total of 100 patients with ventricular septal defect were divided into control group who underwent cardiopulmonary bypass under the guidance of three-dimensional thoracic ultrasound and experimental group of ventricular septal defect occlusion under the guidance of esophageal ultrasound based on artificial fish swarm algorithm. The results showed that the number of successful cases in the experimental group was 12 cases of perimembranous type, 10 cases of septal type, 7 cases of simple membranous type, 13 cases of muscular type, 4 cases of subdry type, and 2 cases of ridge type. The average length of operation after surgery was 70.65 minutes, the average length of ventilator ventilation was 125.8 minutes, and the average length of intensive care unit was 377.9 minutes. The average length of hospital stay after surgery was 5.6 days, and the average total length of hospital stay was 8.2 days, which were better than the control group in many aspects, with statistical significance ( $P<0.05$ ). In short, the artificial fish swarm algorithm for esophageal ultrasound-guided ventricular septal defect closure had short operation time and good postoperative effect, which was of high application value in the clinical treatment of patients with ventricular septal defect.