Application of AI-assisted Breast Ultrasound Technology in Breast Cancer Screening

Abstract

To explore the application effect of artificial intelligence-assisted breast screening ultrasound technology in breast cancer screening. Methods 170 suspected breast cancer patients who underwent breast ultrasound examination in our hospital from July 2022 to June 2024 were retrospectively analyzed, and the results of breast biopsy were taken as the gold standard by physician analysis, artificial intelligence analysis, and combined artificial intelligence analysis. To compare the application effect of ultrasonography in breast cancer screening in three ways. Results Among 170 suspected breast cancer patients, 132 were positive, 38 were negative, 113 were true positive, and 29 were true negative. Sensitivity was 85.61%, specificity was 76.32%, consistency was 83.53%, positive predictive value was 92.62%, and negative predictive value was 60.42%. There were 124 true positive cases and 33 true negative cases, the sensitivity was 93.94%, the specificity was 86.84%, the consistency was 92.35%, the positive predictive value was 96.12%, and the negative predictive value was 80.49%. The results showed that 131 cases were true positive, and 37 were true negative. The sensitivity was 99.24%, the specificity was 97.37%, the consistency was 98.82%, the positive predictive value was 99.24%, and the negative predictive value was 97.37%. Taking the results of breast puncture biopsy as the "gold standard," the diagnostic sensitivity, specificity, consistency, positive predictive value, and negative predictive value of physician-combined artificial intelligence analysis were significantly higher than those of physician-only analysis or artificial intelligence analysis. Conclusion The application of AI-assisted breast screening ultrasound technology to breast cancer screening in our hospital not only helps to realize the consistency and accuracy of early identification and diagnosis of breast cancer so that patients can get more accurate treatment but also helps to reduce the workload of radiologists.