Application of Artificial Intelligence in Human Diagnosis and Public Health Management

Abstract

To improve the diagnostic efficiency and accuracy of corona virus disease 2019 (COVID-19), and to study the application of artificial intelligence (AI) in COVID-19 diagnosis and public health management, the computer tomography (CT) image data of 200 COVID-19 patients are collected, and the image is input into the AI auxiliary diagnosis software based on the deep learning model, "uAI the COVID-19 intelligent auxiliary analysis system", for focus detection. The software automatically carries on the pneumonia focus identification and the mark in batches, and automatically calculates the lesion volume. The result shows that the CT manifestations of the patients are mainly involved in multiple lobes, and in density, the most common shadow is the ground glass opacity. The detection rate of manual detection method is 95.30%, misdiagnosis rate is 0.20% and missed diagnosis rate is 4.50%; the detection rate of AI software focus detection method based on deep learning model is 99.76%, the misdiagnosis rate is 0.08%, and the missed diagnosis rate is 0.08%. Therefore, it can effectively identify COVID-19 focus and provide relevant data information of focus to provide objective data support for COVID-19 diagnosis and public health management.

The communication of artificial intelligence and deep learning in computer tomography image recognition of epidemic pulmonary infectious diseases

“…The results indicated that the two detection methods had the same range of lesion markers. However, the detection rate of the AI detection method based on DL was significantly higher than that of the manual detection method (P<0.05), while the false detection rate and missed diagnosis rate were remarkably lower than that of the manual detection method (P<0.05) [ 24 ].…”