Objective To compare the value of standard deviation(SD)method and root mean square(RMS)method for measuring signal-to-noise ratio(SNR)of MRI of American College of Radiology(ACR)phantom based on phased array coils.Methods ACR phantom was scanned with head coil(Head),abdominal coil(Anterior),dual piece flexible coil(Flex L)and abdominal coil+flexible coil(Anterior+Flex L)each for 6 times,respectively,with sequences of axial T 1W-spin echo(SE)and T2W-SE.And the scanning schemes were divided into 8 groups based on 4 types of coils and 2 sequences.SNR of 8 groups were measured with standard deviation method and root mean square method,respectively,and the differences between the above 2 methods were observed.Results For T1W-SE sequence,SNRsD of MRI based on Head,Anterior,Flex L and Anterior+Flex L was 1.25±0.07,0.56±0.02,1.15±0.10 and 1.04±0.11,respectively,while SNRRMs was 1.10±0.07,0.58±0.03,1.01±0.13 and 1.31±0.15,respectively.For T2W-SE sequence,SNRsD was 1.40±0.08,0.48±0.02,1.04±0.07 and 1.08±0.06,respectively,while SNRRMs was 1.29±0.09,0.53±0.03,0.84±0.08 and 1.35±0.12,respectively.Compared pairwise,significant difference of SNRsD was found in 9 pairs(all P＜0.05),while of SNRRMs was detected in 10 pairs(all P＜0.05).Conclusion Compared with standard deviation method,root mean square method was more suitable for measuring SNR of MRI of ACR phantom based on phased array coils.

[Objective]To study the application effect of the"Learning-Skill-Application"teaching method on enhancing the specialized abilities of resident doctors in residence training.[Methods]A total of 140 resident doctors in residence training who rotated in the Acupuncture and Tuina Department of Jiaxing Hospital of Traditional Chinese Medicine from July 2022 to December 2023 were included and divided into two groups by random number table method.The control group was taught traditionally,and the observation group was taught using the"Learning-Skill-Application"guided teaching method.After the rotation,the resident doctors in residence training were evaluated in multiple dimensions,including basic knowledge,clinical skills and clinical consultation ability(such as medical history collection and physical examination,clinical thinking of traditional Chinese and western medicine,medical records writing).The questionnaire survey was concurrently administered to assess resident doctors'satisfaction with the teaching performance of their clinical instructors.[Results]The observation group demonstrated superior performance in both theoretical basic knowledge exam scores and clinical skills operation scores compared with the control group(P<0.05).Additionally,the observation group exhibited better clinical consultation abilities(P<0.05)and reported higher satisfaction with the teaching methodology than the control group(P<0.05).[Conclusion]In the standardized training of Department of Acupuncture and Moxibustion and Department of Tuina,the"Learning-Skill-Application"guided teaching method is better than the traditional teaching method in improving the specialized ability of resident doctors in residence training,and is worth promoting.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

In recent years,the microorganisms residues in endoscopes have frequently resulted in cross transmis-sion or even the outbreak of hospital-associated infections.It is of great importance to carry out standardized bio-logical surveillance of endoscopes,find out the high-risk links of cleaning and disinfection,and take targeted inter-vention measures to reduce the incidence of endoscopy-related infection.Based on the related guidelines in China and abroad as well as the latest clinical practice researches,the biological surveillance sampling and culture for en-doscopes were summarized in the article so as to enhance the surveillance quality,ensure the reprocessing effect and guarantee the endoscopy-related quality and safety.

Objective:By analyzing peripheral blood indicators, we constructed and validated a novel lung cancer prediction model using machine learning algorithms for riskassessment of lung cancer.Methods:A retrospective case-control design was conducted on the clinical data of 194 newly diagnosed lung cancer patients [mean age: (66.80±9.09) years, 126 males and 68 females] admitted to Qilu Second Hospital of Shandong University between January 9, 2020, and December 31, 2024, serving as the case group. During the same period, 290 healthy individuals undergoing physical examinations [mean age: (61.18±14.31) years, 155 males and 135 females J were enrolled as the control group. A total of 46 peripheral blood indicators-including routine blood tests, coagulation parameters, liver function markers, and tumor-related indices-along with two basic characteristics (age and sex) were included in the analysis. Eleven machinelearning algorithms including logistic regression, randomforest, support vector classifier, extreme gradient boosting, gradient boosting decision tree, decision tree, multilayer perceptron, linear discriminant analysis, adaptive boosting, Gaussian naive Bayes and light gradient-boosting machine-were trained for early diagnosis of lung-cancer.Model performance was evaluated by the area under the ROC, accuracy, positive predictive value, negative predictive value, F1-score and 95% confidence interval (95% CI). The best performing algorithm was selected, and feature importance was ranked with Shapley Additive Planation(SHAP) values. Results:The support-vector classifier achieved the best performance for predicting lung-cancer risk (AUC=0.974; 95 % CI 0.951-0.989) and was retained for final model establishment. After 20 rounds of stratified 10-fold cross-validation the mean AUC was 0.950; learning-curve, decision-curve and calibration analyses confirmed its superior generalizability, clinical utility and calibration.SHAPley additive explanations and decision-tree feature importance consistently identified neuron-specific enolase, carcinoembryonic antigen, and squamous-cell carcinoma antigen as the three most critical predictors of lung-cancer risk. Conclusion:An SVM-based lung cancer prediction model was successfully established to determine the risk of developing lung cancer.

The term yin excess originated in the Huang Di Nei Jing, which refers to the phenomenon of "heavy yin" when wind pathogens invades the human body and defensive qi enters the yin part of the human body. Later doctors have played a role in yin excess. Theoretically, yin and yang are out of balance in the human body, and yin is too much and yang is not enough, which is the process of physiological transformation to pathology; from the diagnosis point of view, patients with yin deficiency have less pulse and more blood; from the clinical manifestations, patients with yin excess appear cold from the back, hands and feet cold reverse; from the point of view of treatment, bitter cold products can cause yin excess. Modern research specifies yin as phlegm, dampness, stasis and other pathological products, and emphasize the relation between yin excess and yang deficiency. Yin excess includes pathological factors such as phlegm stasis cold, external cold straight in the liver wood, set in the hypochasm, resulting in mass; or overthinking and cold drink injury spleen, phlegm turbidiousness, long and hard phlegm forming lumps, thus resulting yin excess; or it may deplete the yang energy of the heart, leading to neglect of the warming function and stagnation of blood stasis; or if the kidney yang is deficient and the body lacks warmth, and there is no true yang in the ridge, then the wood will sink and congest blood stasis; the above etiology and pathogenesis lead to the occupation of yin pathogens, resulting in liver cancer. The treatment methods include liver cold turbidizing, warming liver and dispelling cold, with Wuzhuyu Decoction; spleen-deficiency phlegm production, the treatment should be warm the middle and resolving the phlegm, with Linggui Zhugan Decoction and Zhenwu Decoction; Yang deficiency and stasis, the treatment should warm kidney to remove blood stasis, with Poyu Decoction.

With the advancement of science and technology and the increasing care needs of critically ill patients, critical care nursing robots have developed rapidly. This paper provides an overview of the current applications of nursing robots in intensive care settings, including assessment and monitoring, routine care, rehabilitative care, emotional assistance, remote care, and multifunctional integration. Furthermore, the challenges associated with the implementation of critical care nursing robots and future development directions are discussed, aiming to provide a reference for the optimization and practical application of such technologies.

In recent years,the microorganisms residues in endoscopes have frequently resulted in cross transmis-sion or even the outbreak of hospital-associated infections.It is of great importance to carry out standardized bio-logical surveillance of endoscopes,find out the high-risk links of cleaning and disinfection,and take targeted inter-vention measures to reduce the incidence of endoscopy-related infection.Based on the related guidelines in China and abroad as well as the latest clinical practice researches,the biological surveillance sampling and culture for en-doscopes were summarized in the article so as to enhance the surveillance quality,ensure the reprocessing effect and guarantee the endoscopy-related quality and safety.

Objective To compare the value of standard deviation(SD)method and root mean square(RMS)method for measuring signal-to-noise ratio(SNR)of MRI of American College of Radiology(ACR)phantom based on phased array coils.Methods ACR phantom was scanned with head coil(Head),abdominal coil(Anterior),dual piece flexible coil(Flex L)and abdominal coil+flexible coil(Anterior+Flex L)each for 6 times,respectively,with sequences of axial T 1W-spin echo(SE)and T2W-SE.And the scanning schemes were divided into 8 groups based on 4 types of coils and 2 sequences.SNR of 8 groups were measured with standard deviation method and root mean square method,respectively,and the differences between the above 2 methods were observed.Results For T1W-SE sequence,SNRsD of MRI based on Head,Anterior,Flex L and Anterior+Flex L was 1.25±0.07,0.56±0.02,1.15±0.10 and 1.04±0.11,respectively,while SNRRMs was 1.10±0.07,0.58±0.03,1.01±0.13 and 1.31±0.15,respectively.For T2W-SE sequence,SNRsD was 1.40±0.08,0.48±0.02,1.04±0.07 and 1.08±0.06,respectively,while SNRRMs was 1.29±0.09,0.53±0.03,0.84±0.08 and 1.35±0.12,respectively.Compared pairwise,significant difference of SNRsD was found in 9 pairs(all P＜0.05),while of SNRRMs was detected in 10 pairs(all P＜0.05).Conclusion Compared with standard deviation method,root mean square method was more suitable for measuring SNR of MRI of ACR phantom based on phased array coils.

[Objective]To study the application effect of the"Learning-Skill-Application"teaching method on enhancing the specialized abilities of resident doctors in residence training.[Methods]A total of 140 resident doctors in residence training who rotated in the Acupuncture and Tuina Department of Jiaxing Hospital of Traditional Chinese Medicine from July 2022 to December 2023 were included and divided into two groups by random number table method.The control group was taught traditionally,and the observation group was taught using the"Learning-Skill-Application"guided teaching method.After the rotation,the resident doctors in residence training were evaluated in multiple dimensions,including basic knowledge,clinical skills and clinical consultation ability(such as medical history collection and physical examination,clinical thinking of traditional Chinese and western medicine,medical records writing).The questionnaire survey was concurrently administered to assess resident doctors'satisfaction with the teaching performance of their clinical instructors.[Results]The observation group demonstrated superior performance in both theoretical basic knowledge exam scores and clinical skills operation scores compared with the control group(P<0.05).Additionally,the observation group exhibited better clinical consultation abilities(P<0.05)and reported higher satisfaction with the teaching methodology than the control group(P<0.05).[Conclusion]In the standardized training of Department of Acupuncture and Moxibustion and Department of Tuina,the"Learning-Skill-Application"guided teaching method is better than the traditional teaching method in improving the specialized ability of resident doctors in residence training,and is worth promoting.