OBJECTIVE To construct ensemble learning models for predicting high-use days of budesonide based on meteorological factors， thereby providing reference for hospital pharmacy management. METHODS Meteorological data for 2024 and outpatient budesonide usage data from the jurisdiction of Sanming Hospital of Integrated Traditional Chinese and Western Medicine were collected. High-use days were defined as the 75th percentile of outpatient budesonide usage， and a corresponding dataset was established. The prediction task was formulated as a classification problem， and three ensemble learning models were developed： Random Forest， Extreme Gradient Boosting （XGBoost）， and Histogram-based Gradient Boosting Classifier. Model performance was evaluated using accuracy， precision， recall， F1-score， and log-loss. Model interpretability was analyzed using Shapley Additive Explanations （SHAP）. RESULTS The Histogram-based Gradient Boosting Classifier achieved the best performance （accuracy＝0.75， F1-score＝0.48）， followed by XGBoost （accuracy＝0.74， F1-score＝0.43） and Random Forest （accuracy＝0.72， F1-score＝0.22）. SHAP results suggested that the prediction results of the last two models have the highest correction. CONCLUSIONS Ensemble learning models can effectively predict high-use days of budesonide， with the Histogram- based Gradient Boosting Classifier demonstrating the best predictive performance. Low temperature， high humidity， and low atmospheric pressure show significant positive impacts on the prediction of daily budesonide usage.

Morphea alopecia is a rare secondary cicatricial alopecia, often caused by linear scleroderma of the scalp. When hair loss appears as the only symptom of morphea, it is easily confused with other localized alopecia. The diagnosis of morphea alopecia depends on histopathologic and dermoscopic examinations. In order to improve the understanding of morphea alopecia among clinicians, this review summarizes research progress in its pathogenesis, clinical and pathological characteristics, diagnosis and treatment.

Erosive pustular dermatosis of the scalp (EPDS) is a rare superficial skin inflammatory disease that occurs on the scalp, and its pathogenesis is still unclear. Its clinical manifestations are similar to those of infective inflammation and malignant tumors, and its diagnosis is highly dependent on non-specific pathological changes, so the diagnosis is relatively difficult. Clinically, topical glucocorticoids are the main treatment method, but treatment outcomes vary greatly among individuals, and patients with refractory EPDS need other treatment methods. EPDS generally requires long-term topical glucocorticoid therapy, and adverse drug reactions are common. This review summarizes research progress in EPDS in recent years, in order to improve clinicians' understanding of this disease.

Congenital triangular alopecia is a kind of non-inflammatory and non-cicatricial alopecia, and most cases develop this disease at the ages of 2 - 9 years. The pathogenesis of congenital triangular alopecia is still unclear, and there is a lack of effective treatments. Congenital triangular alopecia is rather liable to be misdiagnosed and erroneously treated, and dermoscopy helps confirm the diagnosis. This review summarizes the progress in the epidemiology, pathogenesis, clinical diagnosis, and treatment of congenital triangular alopecia.

Morphea alopecia is a rare secondary cicatricial alopecia, often caused by linear scleroderma of the scalp. When hair loss appears as the only symptom of morphea, it is easily confused with other localized alopecia. The diagnosis of morphea alopecia depends on histopathologic and dermoscopic examinations. In order to improve the understanding of morphea alopecia among clinicians, this review summarizes research progress in its pathogenesis, clinical and pathological characteristics, diagnosis and treatment.

Erosive pustular dermatosis of the scalp (EPDS) is a rare superficial skin inflammatory disease that occurs on the scalp, and its pathogenesis is still unclear. Its clinical manifestations are similar to those of infective inflammation and malignant tumors, and its diagnosis is highly dependent on non-specific pathological changes, so the diagnosis is relatively difficult. Clinically, topical glucocorticoids are the main treatment method, but treatment outcomes vary greatly among individuals, and patients with refractory EPDS need other treatment methods. EPDS generally requires long-term topical glucocorticoid therapy, and adverse drug reactions are common. This review summarizes research progress in EPDS in recent years, in order to improve clinicians' understanding of this disease.

Congenital triangular alopecia is a kind of non-inflammatory and non-cicatricial alopecia, and most cases develop this disease at the ages of 2 - 9 years. The pathogenesis of congenital triangular alopecia is still unclear, and there is a lack of effective treatments. Congenital triangular alopecia is rather liable to be misdiagnosed and erroneously treated, and dermoscopy helps confirm the diagnosis. This review summarizes the progress in the epidemiology, pathogenesis, clinical diagnosis, and treatment of congenital triangular alopecia.

OBJECTIVE To evaluate the safety and suitability of traditional Chinese medicine prescriptions generated by generative artificial intelligence （AIGC）， and to provide research ideas for empowering the traditional Chinese medicine industry with AIGC. METHODS Using the 2020 edition of Chinese Pharmacopoeia and the 5th edition of Traditional Chinese Medicine as corpus， GPT-4 and the real-time networking model developed based on GPT-4 （referred to as the “networking model”） were used for deep learning. The clinical cases included in the consensus of traditional Chinese medicine experts in recent years were extracted manually to regenerate prescriptions based on diagnosis using the GPT-4 model and networking model； traditional Chinese medicine experts conducted blind evaluation and scoring of GPT-4 generated prescriptions， networking model generated prescriptions， and expert consensus prescriptions. At the same time， Turing testing was used to evaluate whether the GPT-4 model and networking model had the same ability as human intelligence. RESULTS The average score of traditional Chinese medicine prescriptions generated by the GPT-4 model showed no statistically significant difference compared to manual prescriptions （P＞0.05）， while the average score of prescriptions generated by the networking model showed no statistically significant difference compared to traditional Chinese medicine prescriptions generated by the GPT-4 model （P＞0.05）. The proportion of model-generated prescriptions mistakenly judged as manual prescriptions in the Turing test was 51.11%. CONCLUSIONS The traditional Chinese medicine prescriptions generated by the GPT-4 model have reached a certain level of safety and suitability， and the GPT-4 model has passed the Turing test. The introduction of AIGC in the diagnosis and treatment process may provide technical support for the rational use of clinical traditional Chinese medicine.

Frontal fibrosing alopecia is a primary lymphocytic cicatricial alopecia, and is generally considered to be a subtype of lichen planopilaris due to similar histopathological changes. Its etiology is still unclear. With the deepening of research on this disease, more and more cases of frontal fibrosing alopecia have been reported in China and other countries. This review summarizes research progress in pathogenesis, clinical and pathological characteristics, and treatment of frontal fibrosing alopecia.

Objective:To explore the effect of narrative nursing on the psychological resilience, self-esteem, and medication compliance of adolescent depression patients.Methods:This study is a quasi-experimental study. From August 2021 to January 2022, 86 adolescent depression patients admitted to the Department of Mental Health at the First Hospital of Shanxi Medical University were selected as the subject by convenience sampling. According to the order of admission time, the patients were divided into a control group and an intervention group, with 43 patients in each group. The control group received routine nursing, while the intervention group received narrative nursing on the basis of routine nursing. We compared the scores of the Self-Rating Depression Scale (SDS), Hamilton Depression Scale (HAMD), Self-Esteem Scale (SES), Connor-Davidson Resilience Scale (CD-RISC), and Morisky Medication Adherence Scale (MMAS-8) before and after intervention between two groups of patients.Results:Before intervention, there was no statistically significant difference in SDS, HAMD, SES, CD-RISC, and MMAS-8 scores between the two groups ( P>0.05). After intervention, the total scores of SDS and HAMD in the intervention group were lower than those before intervention and in the control group, and the toughness, optimism, self-improvement scores and the CD-RISC total score, SES scores and MMAS-8 scores were higher than those before intervention and in the control group, with statistically significant differences ( P<0.05) . Conclusions:Narrative nursing can improve the depressive mood of adolescent depression patients, enhance their psychological resilience, self-esteem, and medication compliance, and can be promoted and applied in clinical practice.