Purpose/Significance To use multimodal data analysis method to mine medical Q&A data in online healthcare platforms and predict whether patients will adopt online doctors'responses.Method/Process First,numerical,categorical,textual,and visual data related to doctor-patient Q&A are obtained from online healthcare platforms,and three datasets of acute disease,chronic disease and mixed disease are constructed according to disease types.Then,normalization,one-hot encoding,Med-BERT,and convolutional neural network are used respectively to process numerical,categorical,textual,and visual data.Finally,a gradient boosting decision tree is used to predict whether patients will adopt online doctors'responses.Result/Conclusion Doctors'profile pictures can improve the prediction effect of online doctor response adoption,and multimodal data mining can effectively predict the response adoption.

Objective:To investigate the application value of Th1/Th2 cytokines,interleukin-17(IL-17)and serum tumor markers in the diagnosis,prognosis and recurrence of breast cancer.Methods:A total of 200 patients with breast cancer admitted to Inner Mongolia Hospital of Peking University Cancer Hospital from December 2021 to December 2022 were selected,and they were divided into negative group(60 cases),weakly positive(80 cases)group and positive group(60 cases)according to immunohistochemistry indicators.In addition,another 60 persons who underwent physical examination were selected as healthy control group.The changes of the Th1/Th2,IL-17,CA125,CYFRA21-1,CA153 and CEA levels were observed,and the clinical value of the combined detection of the 6 indicators in predicting the prognosis and recurrence of breast cancer was investigated.Results:The results of comparative analysis indicated that the clinical pathological features related to recurrence,histological grading,tumor diameter and lymph node metastasis(x2=7.552,12.037,12.063,8.543,P＜0.05),respectively.Multivariate analysis showed that tumor recurrence,tissue grading,tumor diameter and lymph node metastasis were the important factors for the prognosis of patients with breast cancer(OR=3.096,3.050,3.425,3.031,P＜0.05).Compared with the single prediction of Th1/Th2,IL-17,CA125,CYFRA21-1,CA153 and CEA,the combined prediction of 6 indicators had higher clinical value for prognosis and recurrence of patients with breast cancer,which sensitivity,accuracy and specificity were respectively 96%,93.46%and 85%.Conclusion:The observation on the changes of the combined predictive levels of 6 items,which include Th1/Th2,IL-17,CA125,CYFRA21-1,CA153 and CEA of patients,indicates that the combined detection has high sensitivity and accuracy.This highly efficient and convenient detection method can provide references for improving the prognosis,reducing the recurrence and enhancing the accuracy of assessment.

Sepsis-associated liver injury (SALI) is a common complication of sepsis, which is characterized by systemic immune disorders induced by sepsis leading to liver damage. Currently, there are no effective treatments for SALI, which is related to its complex pathophysiological mechanisms. In recent years, the disorder of intestinal environment after sepsis has been considered as an important factor for SALI, but the specific molecular mechanism of the above process is still unclear. This article will review the pathological role and molecular mechanisms between intestinal environmental disturbance and SALI, aiming to analyze the potential research direction of SALI and identify potential therapeutic targets for its treatment.

Cardiac surgery-associated acute kidney injury(CSA-AKI)is a common and serious complication following cardiac surgical procedures.The conventional diagnostic methods relying on serum creatinine and urine output changes often exhibit delayed responsiveness.Therefore,there is an urgent need for highly sensitive and specific biomarkers to detect and identify high-risk patients with CSA-AKI at an early stage,allowing for timely intervention and improved clinical outcomes.In this paper,the relevant biomarkers of CSA-AKI were reviewed in order to provide valuable informa-tion for the subsequent research on CSA-AKI.

Cardiac surgery-associated acute kidney injury(CSA-AKI)is a common and serious complication following cardiac surgical procedures.The conventional diagnostic methods relying on serum creatinine and urine output changes often exhibit delayed responsiveness.Therefore,there is an urgent need for highly sensitive and specific biomarkers to detect and identify high-risk patients with CSA-AKI at an early stage,allowing for timely intervention and improved clinical outcomes.In this paper,the relevant biomarkers of CSA-AKI were reviewed in order to provide valuable informa-tion for the subsequent research on CSA-AKI.

Brain-computer interfaces (BCIs) have become one of the cutting-edge technologies in the world, and have been mainly applicated in medicine. In this article, we sorted out the development history and important scenarios of BCIs in medical application, analyzed the research progress, technology development, clinical transformation and product market through qualitative and quantitative analysis, and looked forward to the future trends. The results showed that the research hotspots included the processing and interpretation of electroencephalogram (EEG) signals, the development and application of machine learning algorithms, and the detection and treatment of neurological diseases. The technological key points included hardware development such as new electrodes, software development such as algorithms for EEG signal processing, and various medical applications such as rehabilitation and training in stroke patients. Currently, several invasive and non-invasive BCIs are in research. The R&D level of BCIs in China and the United State is leading the world, and have approved a number of non-invasive BCIs. In the future, BCIs will be applied to a wider range of medical fields. Related products will develop shift from a single mode to a combined mode. EEG signal acquisition devices will be miniaturized and wireless. The information flow and interaction between brain and machine will give birth to brain-machine fusion intelligence. Last but not least, the safety and ethical issues of BCIs will be taken seriously, and the relevant regulations and standards will be further improved.
Humans ; Brain-Computer Interfaces ; Medicine ; Algorithms ; Artificial Intelligence ; Brain