Annals of medicine
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Most infectious diseases are caused by viruses, fungi, bacteria and parasites. Their ability to easily infect humans and trigger large-scale epidemics makes them a public health concern. Methods for early detection of these diseases have been developed; however, they are hindered by the absence of a unified, interoperable and reusable model. This study seeks to create a holistic and real-time model for swift, preliminary detection of infectious diseases using symptoms and additional clinical data. ⋯ The graph-based MLP and RF models effectively diagnosed influenza and hepatitis, respectively. This underlines the potential of graph data science in enhancing ML model performance and uncovering concealed relationships in the MKG.
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To investigate the application value of tumor abnormal protein in patients with type 2 diabetes mellitus complicated with lung adenocarcinoma in situ. ⋯ Therefore, detecting tumor abnormal protein levels may help diagnose lung adenocarcinoma in situ in patients with type 2 diabetes mellitus.
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Cancer-associated fibroblasts (CAFs) are the most important components of the tumor microenvironment (TME). CAFs are heterogeneous and involved in tumor tumorigenesis and drug resistance, contributing to TME remodeling and predicting clinical outcomes as prognostic factors. However, the effect of CAFs the TME and the prognosis of patients with breast cancer (BC) is not fully understood. This study investigated the correlation between CAFs-activating biomarkers immune cell infiltration and survival in patients with breast cancer. ⋯ This study found that CAFs may participate in immunosuppression and regulate tumor cell proliferation and invasion. High TNC expression is associated with several adverse clinicopathological features, and high TNC expression in tumor cells has been identified as an independent prognostic factor for IDC-NOS.
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Low cardiac output syndrome (LCOS) is a severe complication after valve surgery, with no uniform standard for early identification. We developed interpretative machine learning (ML) models for predicting LCOS risk preoperatively and 0.5 h postoperatively for intervention in advance. ⋯ The first interpretable ML tool with two prediction periods for online early prediction of LCOS risk after valve surgery was successfully built in this study, in which the SVM model has the best performance, reserving enough time for early precise intervention in critical care.
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This retrospective cohort study aimed to determine the prevalence of precancerous or malignant lesions of the cervix and/or endometrium among patients who underwent vaginal hysterectomy. ⋯ It is possible to detect a minor prevalence of precancerous and malignant lesions following post-operative procedures in POP. The assessment of the elderly through the use of risk-based evaluation merits attention for the purpose of early identification. This study offers valuable insights that can be utilized in preoperative counseling and enhancing the preoperative evaluation process.