[Prediction of color simulation prescription for traditional Chinese medicine placebo solution based on whale algorithm-optimized back propagation neural network].

Traditional Chinese medicine(TCM) placebos are simulated preparations for specific objects and the color simulation in the development of TCM placebos is both crucial and challenging. Traditionally, the prescription screening and pattern exploration process involves extensive experimentation, which is both time-consuming and labor-intensive. Therefore, accurate prediction of color simulation prescriptions holds the key to the development of TCM placebos. In this study, we efficiently and precisely predict the color simulation prescriptions of placebos using an image-based approach combined with Matlab software. Firstly, images of TCM placebo solutions are captured, and 13 chromaticity space values such as the L* a* b*, RGB, HSV, and CMYK values are extracted using Photoshop software. Correlation analysis and normalization are then performed on these extracted values to construct a 13×9×3 back propagation(BP) neural network model. Subsequently, the whale optimization algorithm(WOA) is employed to optimize the initial weights and thresholds of the BP neural network. Finally, the optimized WOA-BP neural network is validated using three representative instances. The training and prediction results indicate that, compared to the BP neural network, the WOA-BP neural network demonstrates superior performance in predicting the pigment ratios of placebos. The correlation coefficients for training, validation,testing, and the overall dataset are 0. 95, 0. 87, 0. 95, and 0. 95, respectively, approaching unity. Furthermore, all error values are reduced, with the maximum reduction reaching 99. 83%. The color difference(ΔE) values for the three validation instances are all less than 3, further confirming the accuracy and practicality of the WOA-BP neural network approach.

A glimpse into the psychological status of E.N.T inpatients in China: A cross-sectional survey of three hospitals in different regions.

OBJECTIVE: To determine whether E.N.T inpatients have a higher prevalence of mental illness than the general population and whether certain diseases are more likely to be associated with mental illness than other diseases. METHODS: This cross-sectional survey was conducted in the E.N.T departments of three hospitals in different cities in China. The psychological status of all consecutive adult inpatients was assessed within 1-2 days following hospital admission using the Symptom Checklist-90 (SCL-90), Zung Self-Rating Depression Scale (SDS) and Zung Self-Rating Anxiety Scale (SAS). Inpatients from the general surgery and pneumology departments at the same hospital were enrolled and surveyed as control groups. RESULTS: The 439 patients enrolled in the final analysis accounted for 88.0% of all E.N.T inpatients during the study period. Of these patients, 16.4% were in an anxious state and 79.5% were in a depressive state. The overall anxiety (41.7 ± 9.7) and depression (55.9 ± 29.2) scores were much higher than Chinese norm (29.8 ± 10.0 and 33.5 ± 8.6, respectively), and significant differences were observed (t = 20.89, P < 0.01 and t = 13.12, P < 0.01, respectively). Although 18.7% of the E.N.T patients were psychiatric distress, these patients scored lower on the SCL-90 than the Chinese norm. Furthermore, the patients in the E.N.T department had a higher prevalence of anxiety and depression than those in the general surgery department but a similar prevalence to those in the respiratory department. CONCLUSION: Psychological distress, particularly anxiety and depression, are widespread in patients with otolaryngological diseases. Therefore, the identification and treatment of co-occurring psychiatric disorders in this high risk and clinically challenging group of patients are urgent in China.