Objective To explore the feasibility of bilingual teaching in the course of Physical Therapy, and find out the more suitable program of the bilingual teaching for undergraduate students of rehabilitation therapy. Methods Students of rehabilitation therapy from Capital Medical University School of Rehabilitation Medicine were randomly divided into two groups: experimental group received bilingual education during the teaching session, while the students in control group received traditional teaching method. Their scores of the quiz were compared, and the students were investigated with the questionnaire. Results The scores of English quiz were higher in the experimental group than in the control group (P<0.05), but there was no significant difference of the total score between two groups. The results of questionnaire showed that the bilingual education was accepted by most students. Conclusion Bilingual teaching program could facilitate the improvement of the student's ability, and it will be more suitable for undergraduate students of rehabilitation therapy.

OBJECTIVE: In order to improve the accuracy of the current pulmonary nodule location detection method based on CT images, reduce the problem of missed detection or false detection, and effectively assist imaging doctors in the diagnosis of pulmonary nodules. METHODS: Propose a novel method for detecting the location of pulmonary nodules based on multiscale convolution. First, image preprocessing methods are used to eliminate the noise and artifacts in lung CT images. Second, multiple adjacent single-frame CT images are selected to be concatenate into multi-frame images, and the feature extraction is carried out through the artificial neural network model U-Net improved by multi-scale convolution to enhanced feature extraction capability for pulmonary nodules of different sizes and shapes, so as to improve the accuracy of feature extraction of pulmonary nodules. Finally, using point detection to improve the loss function of U-Net training process, the accuracy of pulmonary nodule location detection is improved. RESULTS: The accuracy of detecting pulmonary nodules equal or larger than 3 mm and smaller than 3 mm are 98.02% and 96.94% respectively. CONCLUSIONS This method can effectively improve the detection accuracy of pulmonary nodules on CT image sequence, and can better meet the diagnostic needs of pulmonary nodules.
Humans ; Lung Neoplasms/diagnostic imaging* ; Solitary Pulmonary Nodule/diagnostic imaging* ; Tomography, X-Ray Computed ; Neural Networks, Computer

OBJECTIVE: To use the low-cost anesthesia monitor for realizing anesthesia depth monitoring, effectively assist anesthesiologists in diagnosis and reduce the cost of anesthesia operation. METHODS: Propose a monitoring method of anesthesia depth based on artificial intelligence. The monitoring method is designed based on convolutional neural network (CNN) and long and short-term memory (LSTM) network. The input data of the model include electrocardiogram (ECG) and pulse wave photoplethysmography (PPG) recorded in the anesthesia monitor, as well as heart rate variability (HRV) calculated from ECG, The output of the model is in three states of anesthesia induction, anesthesia maintenance and anesthesia awakening. RESULTS: The accuracy of anesthesia depth monitoring model under transfer learning is 94.1%, which is better than all comparison methods. CONCLUSIONS The accuracy of this study meets the needs of perioperative anesthesia depth monitoring and the study reduces the operation cost.
Artificial Intelligence ; Neural Networks, Computer ; Heart Rate ; Electrocardiography ; Photoplethysmography/methods* ; Anesthesia

Objective:To evaluate the pancreatic subclinical dysfunction after intensity-modulated radiation therapy (IMRT) for gastric cancer by analyzing biochemical indexes and pancreatic volume changes, and to reduce the dose of pancreas by dosimetric prediction and dose limitation.Methods:30 patients with gastric cancer who received 45 Gy postoperative adjuvant radiotherapy were retrospectively selected. The pancreas was delineated and its dose and anatomical relationship with planning target volume (PTV) were evaluated. Fasting blood glucose, serum lipase and amylase, and pancreatic volume changes before and after radiotherapy were analyzed. The correlation between the changes of biochemical indexes and volume and pancreatic dose was evaluated by Pearson analysis. The threshold of the dosimetric prediction was obtained by receiver operating characteristic (ROC) curve. Finally, the feasibility of dosimetric limitation in IMRT was assessed.Results:The pancreatic volume of 30 patients was 37.6 cm 3, and 89.0% of them were involved in PTV. D mean of the pancreas was 45.92 Gy, and 46.45 Gy, 46.46 Gy and 45.80 Gy for the pancreatic head, body and tail, respectively. The fasting blood glucose level did not significantly change. The serum lipase levels were significantly decreased by 66% and 77%(both P<0.001), and the serum amylase levels were significantly declined by 24% and 38%(both P<0.001) at 6 and 12 months after radiotherapy. Pancreatic volumes of 22 patients was decreased by 47% within 18 months after radiotherapy. ROC curve analysis showed that pancreatic V 45Gy had the optimal predictive value for the decrease by 1/3 of serum lipase and amylase levels at 6 months and serum amylase level at 12 months after radiotherapy, and the cut-off value was V 45Gy<85%. Pancreatic D mean yielded the optimal predictive value for the decrease by 2/3 of serum lipase level at 12 months after radiotherapy, and the cut-off value was D mean<45.01 Gy. After" whole pancreas" and" outside PTV pancreas" dose limit, V 45Gy of the pancreas was decreased by 11% and 7%, D mean of the pancreas was declined by 2% and 2%, and D mean of the pancreatic tail was decreased by 3%, respectively. Conclusions:Serum lipase and amylase levels significantly decline at 6 and 12 months after adjuvant radiotherapy for gastric cancer, and pancreatic volume is decreased significantly within 18 months after radiotherapy. Pancreatic V 45Gy<85% and D mean<45.01 Gy are the dose prediction values for the decrease of serum lipase and amylase levels. The dose can be reduced to certain extent by dosimetric restriction.