Objective:To aid in the detection of thyroid cancer by using deep learning to differentiate the unique bioimpedance parameter patterns of different thyroid tissues.Methods:An electrical impedance system was designed to measure 331 ex-vivo thyroid specimens from 321 patients during surgery. The impedance data was then analyzed with one dimensional convolution neural (1D-CNN) combining with long short-term memory (LSTM) network models of deep learning. In the process of analysis, we assigned 80% of the data to training set (1072/1340) and the remaining 20% data to the test set (268/1340). The performance of final model was assessed using receiver operating characteristic (ROC) curves. In addition, sensitivity, specificity, positive predictive value, negative predictive value, Youden index were applied to compare impedance model with ultrasound results.Results:The ROC curve of the two-classification (malignant /non-malignant tissue) model showed a good performance (area-under-the-curve AUC=0.94), with an overall accuracy of 91.4%. To better fit clinical practice, we further performed a three-classification (malignant/ benign/ normal tissue) model, of which the areas under ROC curve were 0.91, 0.85, 0.92 for normal, benign, and malignant group, respectively. The results indicated that the area under micro-average ROC curve and the macro-average ROC curve were 0.91 and 0.90, respectively. Moreover, compared with ultrasound, the impedance model exhibited higher specificity.Conclusions:A deep learning model (CNN-LSTM) trained by thyroid electrical impedance spectroscopy (EIS) parameters shows an excellent performance in distinguishing among different in-vitro thyroid tissues, which is promising for applications. In future clinical utility, our study does not replace existing tests, but rather complements others, thus contributing to therapeutic decision-making and management of thyroid disease.

Objective:To analyze the changing trend of intracerebral hemorrhage (ICH) incidence among residents with different characteristics during 9 years of comprehensive hypertension prevention and control (hypertension prevention and control) in Tengzhou from 2013 to 2021.Methods:From January 1, 2013 to December 31, 2021, the new ICH cases collected by the Center for Disease Control and Prevention in Tengzhou City were analyzed to calculate the incidence of ICH, and the trend of its distribution was analyzed among residents with different ages, sexes, and between urban and rural areas. The registered population information came from Tengzhou Public Security Bureau. Age and sex standardized incidence was calculated based on the 7th National Population Census in 2020. The Cochran-Armitage test was used to analyze the time and age trends of the incidence.Results:The overall ICH crude and standardized incidence in Tengzhou City decreased from 97.30/100 000 to 52.13/100 000 ( Z=-9.93, P<0.001) and 119.30/100 000 to 50.69/100 000 ( Z=-15.40, P<0.001) from 2013 to 2021, and both elevated to form a single peak in 2020, with 22.58% ( χ 2=24.02, P<0.001) and 18.09% ( χ 2=17.08, P<0.001) higher than in 2019, respectively. The trends in male and female incidence over the same period were similar to the overall trends, and the incidence was higher in males than in females in all years. The incidence of ICH increased with age in all years. The difference of increase in male incidence rate in 2020 was statistically significant in three age groups ≥45 years compared with 2019 (36.29%, 23.57% and 16.18%, respectively, χ 2=6.73, 4.65, 4.00, P<0.001). The incidence of ICH decreased by 70.07% and 36.23% ( Z=18.44, 5.22, P<0.001) in urban and rural areas respectively from 2013 to 2021, whereas increased by 34.15% ( χ 2=10.88, P<0.01) and 22.08% ( χ 2=18.63, P<0.001) in 2020 compared with 2019 separately. Conclusions:The incidence of ICH in Tengzhou from 2013 to 2021 showed a significant downward trend, with the decrease in the incidence of ICH in women exceeding that in men. The decrease in the incidence of ICH in urban areas exceeded that in rural areas, and male morbidity seemingly had a younger trend.

Purpose To explore the artificial intelligence(AI)-assisted diagnosis system of thyroid cancer based on deep transfer learning and evaluate its clinical application value.Methods The HE sections of 682 cases thyroid disease patients(including benign lesions,papillary carcinoma,follicular carci-noma,medullary carcinoma and undifferentiated carcinoma)in the Pathology Department of the Renmin Hospital of Wuhan Uni-versity were collected,scanned into digital sections,divided into training sets and internal test sets according to the ratio of 8 ∶ 2,and the training sets were labeled at the pixel level by patholo-gists.The thyroid cancer classification model was established u-sing VGG image classification algorithm model.In the process of model training,the parameters of the breast cancer region recog-nition model were taken as the initial values,and the parameters of the thyroid cancer region recognition model were optimized through the transfer learning strategy.Then the test set and 633 intraoperative frozen HE section images of thyroid disease in Jianli County People's Hospital,Jingzhou City,Hubei Province wereused as the external test set to evaluate the performance of the established AI-assisted diagnostic model.Results In the internal test set,without the use of the breast cancer region rec-ognition model transfer learning,the accuracy of the AI-assisted diagnosis model was 0.882,and the area under the Receiver op-erating characteristic(AUC)valuewas0.938;However,inthe use of the Transfer learning model,the accuracy of the AI-assis-ted diagnosis model for was 0.926,and the AUC value was 0.956.In the external test set,the accuracy of the zero learning model was 0.872,the AUC value was 0.915,and the accuracy of the Transfer learning model was 0.905,the AUC value was 0.930.Conclusion The AI-assisted diagnosis method for thy-roid cancer established in this study has good accuracy and gen-eralization.With the continuous development of pathological AI research,transfer learning can help improve the performance and generalization ability of the model,and improve the accura-cy of the diagnostic model.

Objective:The residual cancer burden (RCB) evaluation system was used to analyze the influencing factors of the efficacy of neoadjuvant therapy in breast cancer, and to explore the prognostic value of RCB evaluation in neoadjuvant therapy.Methods:Clinicopathologic data and postoperative RCB grading of 364 breast cancer patients who underwent neoadjuvant therapy in Renmin Hospital of Wuhan University from Nov. 2019 to Nov. 2022 were collected. Chi-square test was used to analyze the relationship between RCB grading and clinicopathological parameters, and Spearman’s rank correlation analysis was performed to evaluate the correlation between RCB grading and clinicopathological characteristics. Factors influencing pathologic complete response (pCR) were analyzed by Logistic regression. Kaplan-Meier survival analysis and log-rank test were used to evaluate cumulative survival.Results:Among the 364 patients who underwent neoadjuvant therapy, 129 cases of RCB grade 0 and 235 cases of RCB gradeⅠ-Ⅲ (including 46 cases of RCB gradeⅠ, 109 cases of RCB grade Ⅱ and 80 cases of RCB grade Ⅲ) were obtained after surgery. Histological classification ( χ 2=21.757, P=0.000), estrogen receptor (ER) ( χ 2=52.837, P=0.000), progesterone receptor (PR) ( χ 2=55.658, P=0.000), human epidermal growth factor receptor-2 (HER2) ( χ2=89.040, P=0.000), Ki67 expression ( χ2=12.927, P=0.005), molecular typing ( χ 2=80.793, P=0.000) and preoperative lymph node status ( χ 2=25.764, P=0.000) were all associated with postoperative RCB grading. Further correlation analysis showed that histological grade ( r=-0.229, P=0.000), HER2 expression ( r=-0.465, P=0.000) and Ki67 expression ( r=-0.179, P=0.000) were negatively correlated with RCB grading, while ER ( r=0.352, P=0.000), PR ( r=0.379, P=0.000) and lymph node metastasis ( r=0.214, P=0.000) were positively correlated with RCB grading. Logistic regression analysis showed that high histological grade, negative expression of ER, PR and AR, positive expression of HER2, high proliferation index of Ki67 and no lymph node metastasis were favorable factors for postoperative pCR, and PR, AR and HER2 were independent predictors of postoperative pCR. Kaplan-Meier survival analysis showed significant differences in postoperative cumulative survival among patients with different RCB grades ( P=0.004) . Conclusions:Postoperative RCB grading of breast cancer is closely related to many clinicopathological features before neoadjuvant therapy and survival prognosis. Clinicopathological factors closely related to RCB grading are also important influencing factors affecting the pCR of patients with neoadjuvant therapy. Therefors, RCB grading has a high prognostic value.

Objective:Objective To explore the special role of nutrition specialists in the one-day-care clinic of gestational diabetes mellitus (GDM), and provide a basis for strengthening the standardized construction of one-day-care clinic.Methods:It was a retrospective observation study that the pregnant women who participated in the one-day-care clinic of GDM in our hospital without nutrition specialists in November and December 2017 were divided into control group (177 cases), and who participated in the one-day-care clinic of GDM in our hospital with nutrition specialists in January and February 2018 were divided into observation group (307 cases). The differences of pregnancy outcomes between the two groups were compared after the propensity score matching.Results:176 pairs of patients were successfully matched with a 1:1 propensity score. The incidence of macrosomia in pregnant women with GDM in the observation group (2.8%) was significantly lower than that in the control group (8.5%) ( P=0.036). There were no significant differences in the weight gain during pregnancy, the gestational week of delivery and the incidences of insulin use, hypertension during pregnancy, preeclampsia, cesarean section, premature infants, premature rupture of membranes, umbilical cord around the neck, and fetal distress between the two groups ( P>0.05). Conclusion:Nutrition specialists are indispensable in the multidisciplinary cooperation of one-day-care clinic of GDM, and they play a key role in considerably lowering the prevalence of macrosomia in GDM pregnant women.

Objective: To understand the current situation and associated factors of myopia in junior middle school students, and to provide scientific basis for prevention and control of myopia in junior middle school students. Methods: A total of 5 393 junior middle school students were selected from middle schools in Guangdong, Guangxi, Guizhou, Liaoning, Shandong, Shanxi provinces. The visual acuity of middle school students was examined, and the data of general population, economy, sociology and natural environment were obtained through statistical yearbook of each province. The influencing factors of myopia of middle school students were analyzed by univariate and multivariate Logistic regression. Results: The results of single factor analysis showed that the myopia rate of junior high school students was different by gender, grades, parents average wage, sunshine duration, temperature, altitude, longitude and latitude(χ2=47.76，59.05，10.79，106.19，53.56，85.02，76.23，107.07，P<0.05). The results of multi factor analysis showed that gender, grade, average wage, temperature and latitude was positively associated with myopia vision; sunshine duration and longitude were negatively associated with the risk for myopia(OR=1.54，1.34，1.62，7.58，27.10，0.42，0.39，P<0.05). Conclusion The myopia of junior high school students is affected by a variety of factors, economic and social factors and natural environmental factors have an impact on the screening of sexual myopia in junior high school students. Economic and social factors and natural environmental factors should be taken into account in the formulation of myopia prevention and control measures.

A large amount of information, such as clinical hematological data and imaging images, can be extracted by artificial intelligence to form various quantifiable features, analyze the association between different features and problems concerned (such as diagnosis), and thus solve complex medical problems. This article elaborates on the efficiency of various artificial intelligence algorithms in the diagnosis of pancreatic cancer, hepatic fibrosis, and esophageal varices, so as to help clinicians with clearer understanding and better decision-making.

Coronavirus disease 2019 caused by severe acute respiratory syndrome coronavirus 2 has become a serious threat to global public health security. Besides lung diseases, severe cases are also accompanied by varying degrees of liver injury. Previous studies have shown that patients infected with severe acute respiratory syndrome coronavirus and Middle East respiratory syndrome coronavirus may also suffer from liver injury, which is closely associated with disease severity. This article elaborates on the clinical features and pathogenesis of liver injury caused by these three types of highly pathogenic human coronavirus, in order to help clinicians better understand this disease and make accurate decisions.

Objective: To understand the current situation and associated factors of myopia among primary school students, and to provide scientific basis for prevention and control of myopia among primary school students. Methods: In Gansu, Guangdong, Guangxi, Guizhou, Liaoning, Shandong, Shanxi and other provinces, 1 prefecture was selected, and a number of primary schools were selected from each region. All the students in the class were selected as the object of this survey. A total of 8 365 middle school students were examined for their eyesight, and the data of general population economic indicators and natural environment indicators were obtained through the statistical yearbook of various provinces and cities. The influencing factors of primary school students myopia were analyzed by chi-square test and multivariate Logistic regression. Results: Univariate analysis showed that different provinces and different sex, different nationalities, different grade, parents average salary, sunshine duration, air temperature, altitude, longitude, latitude, different economic zone(χ2=116.22, 18.08, 26.33, 1 059.04, 14.86, 10.28, 16.95, 10.01, 23.15, 29.43, 88.14, P<0.05). Multivariate analysis results showed that gender, grade, sunshine duration, longitude were risk factor for poor vision(OR=1.31, 1.71, 1.45, 1.54, P<0.05); Economic zone and parents salary were protective factors for poor eyesight of students (OR=0.65, 0.86, P<0.05). Conclusion Myopia of primary school students is affected by a variety of factors, economic and social factors and natural environmental factors have an impact on the screening.

Objective:To understand the driving factors of postpartum health promotion behaviors in pregnant women with gestational diabetes.Methods:From September to October 2019, the purpose of the sampling method was to select 14 cases of gestational diabetic gynaecologists who visited the outpatient department of diabetes care in our hospital as the research subjects. The phenomenological research method was used to conduct a semi-structured interview. Colaizzi′s 7-step analysis method was used to organize and analyze the data to refine the subject.Results:The driving force of postpartum health promotion behaviors of gestational diabetes mothers mainly came from the internal driving force and the external driving force. The internal driving force was mainly the uncertainty of gestational diabetes, the solution of the problem improves self-worth, and the post-traumatic growth made patients re-understand life. The external driving force was mainly family support, full mobilization of subjective initiative, quantitative diet intake and building of a healthy lifestyle.Conclusions:The driving factors for postpartum health promotion of gestational diabetic women are complex and diverse. Medical staff should timely grasp the post-natal health promotion status of gestational diabetic women, and promote their self-support and social support.