Genetic Algorithm-Based Computed Tomography Image Analysis for the Diagnosis and Mental Health of COVID-19 Patients in Early Low-Incidence Areas

• Main Authors: Yuan Niu, Xuejie He, Guijuan Hao, Liang Wang
• Format: Article
• Language: English
• Published: Hindawi Limited 2021-01-01
• Series: Scientific Programming
• Online Access: http://dx.doi.org/10.1155/2021/2297206

The purpose of this study was to investigate the diagnosis of patients in the early low-incidence area of coronavirus disease 2019 (COVID-19) and the mental health of staff based on genetic algorithm- (GA-) based computed tomography (CT) images. In this study, 136 COVID-19 patients admitted to our hospital were divided into a critical group (94 cases) and a general group (42 cases). In addition, a questionnaire was used to investigate the mental health of COVID-19 patients in early low-incidence areas, including 147 medical staff members and 213 nonmedical staff members. The effects were compared between the optimized GA template matching (OGATM) algorithm proposed in this study and traditional GATM, which were applied in CT images of COVID-19 patients. The results showed that the proposed algorithm could improve the accuracy of pneumonia detection and reduce the false-positive rate. The average age of patients in the severe group was markedly higher than that of the general group (P<0.05). The number of cases with diabetes mellitus (49.6%) from the severe group was more than that from the general group (12.4%) (P<0.05). Lymphocyte count in patients from the severe group (0.68 ± 0.26 × 109/L) was sharply lower than that of the general group (1.12 ± 0.34 × 109/L) (P<0.05). The total T lymphocyte count in patients from the severe group reduced steeply in contrast to that of the general group (P<0.05). The anxiety and depression scores of medical patients (39.45 ± 9.45 points and 47.58 ± 10.47 points) were obviously lower than the scores of nonmedical patients (43.57 ± 9.54 points and 52.48 ± 10.25 points) (P<0.05). In conclusion, the elderly and staffs with diabetes mellitus were more likely to develop severe COVID-19. Moreover, the total T lymphocytes of COVID-19 patients were lower than their normal levels, and nonmedical staffs had more psychological stress than medical staffs.