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The rapid development of technology allows people to obtain a large amount of data, which contains important information and various noises. How to obtain useful knowledge from data is the most important thing at this stage of machine learning (ML). The problem of unbalanced classification is currently an important topic in the field of data mining and ML. At present, this problem has attracted more and more attention and is a relatively new challenge for academia and industry. The problem of unbalanced classification involves classifying data when there is insufficient data or severe category distribution deviations. Due to the inherent complexity of unbalanced data sets, more new algorithms and tools are needed to effectively convert a large amount of raw data into useful information and knowledge. Unbalanced data set is a special case of classification problem, in which the distribution between classes is uneven, and it is difficult to classify data accurately. This article mainly introduces the research on the processing method of computer algorithms based on the processing method of unbalanced data sets based on ML, aiming to provide some ideas and directions for the processing of computer algorithms based on unbalanced data sets based on ML. This article proposes a research strategy for processing unbalanced data sets based on ML, including data preprocessing, decision tree data classification algorithm, and C4.5 algorithm, which are used to conduct research experiments on processing methods for unbalanced data sets based on ML. The experimental results in this article show that the accuracy rate of the decision tree C4.5 algorithm based on ML is 94.80%, which can be better used for processing unbalanced data sets based on ML.

The price of the product has a great impact on the market competitiveness of the product. The manager can adjust the operation strategy according to the cost information of the product, cut costs, adjust the market decision and make the product more competitive in the market. Therefore, the research of product costing method has a very important significance. Considering that the physical resources in the processing of the virtual network mapping (VNM) fragment embedded in the request are rejected, and the problem of physical resource usage is weakened, a VNM algorithm based on the optimal subnet edge matching algorithm is proposed. After the VNM request is coarsened to the subnet, the breadth-first search algorithm is used to create the physical subnet candidate set, and the constraints of the virtual node and the coarsening network topology are complied with. The simulation results show that the proposed algorithm reduces the number of link mapping hops and can improve the acceptance rate and cost-benefit ratio of virtual networks. First of all, this paper analyzes the research background of manufacturing cost calculation and the research situation at home and abroad, discusses the advantages and disadvantages of standard cost calculation and studies and analyzes the principles, advantages and disadvantages of standard cost calculation in daily business activities. Second, design a new mathematical accounting model based on the mathematical model of standard cost calculation in daily business activities. This combines the advantages of standard costing and time-based activity costing, and provides theoretical support for manufacturing companies to use this accounting method. Finally, the research results of this paper are summarized, and the shortcomings of this paper are analyzed. Cost accounting method needs to be further studied. [ABSTRACT FROM AUTHOR]

To enhance public health and reduce medical costs, this paper employs a knowledge map to establish a virtual health community. It integrates valuable medical knowledge using a knowledge fusion algorithm and facilitates online interaction among patients. Utilizing the K-means Clustering Algorithm (K-MEANS) in clustering analysis, users’ needs are consolidated, leading to the creation of a personalized recommendation platform tailored to users’ requirements. The test results show that (1) Angiotensin-Converting Enzyme Inhibitors (ACEI) drugs are effective in treating diabetes and hyperlipidemia, the complications of hypertension, and the trust function values are all above 40%. Calcium Channel Blocker (CCBs) drugs only perform well in the treatment of coronary heart disease, with the trust function value of 47.6%, and the trust function of other hypertension complications does not exceed 30%. Angiotensin Receptor Blocker (ARB) drugs have excellent performance in urine protein, and the trust function value is as high as 52.2%. (2) The accuracy score of the recommended model under K-MEANS decreases with the increase of the number of neighbors and reaches the lowest value when the number of neighbors is 40. The lower the score, the better the accuracy of the model, and the sparsity score of the model data decreases from 10 to 35. However, when the number of neighbors is 35, the score rises, and the overall sparsity score of the model is low, which proves that the model has the ability to deal with data sparsity and makes personalized recommendation of virtual health community more accurate. The objective of this paper is to promote the dissemination of medical knowledge, cater to diverse medical needs, boost online interaction between doctors and patients, enhance the accessibility of healthcare, and contribute to the advancement of public health through personalized recommendations and knowledge integration. [ABSTRACT FROM AUTHOR]

The study aims to investigate the integration of artificial intelligence technology into Weibo sentiment analysis, aiming to enhance the effectiveness of Weibo in human-computer interaction education. Initially, the Weibo sentiment dictionary is created, and a conventional model for sentiment analysis of user-forwarded Weibo is introduced, specifically the Latent Dirichlet Allocation (LDA) model. Then, the deep learning models in the field of artificial intelligence, namely, the convolutional neural network (CNN) model and the long short-term memory network (LSTM) model, are proposed. Tencent Weibo data set is obtained through Application Programming Interface (API) crawler. The experimental environment of the deep learning model is analyzed and the data set is preprocessed. The results show that when the number of topics is 120, the relative maximum value of F1 is 69.92% and 69.96% with and without the introduction of emotional features in the LDA model, respectively. The accuracy of CNN model and LSTM model is 0.793 and 0.849, respectively. In the three cases of user characteristics, user characteristics + Weibo features, and use characteristics + Weibo features + relationship characteristics, the polarity of the forwarded comments of the LDA model doesn’t change much. In conclusion, the LDA model demonstrates universality and accuracy in sentiment analysis of user-forwarded Weibo, while LSTM proves to be more suitable for sentiment classification in this context. Leveraging the LDA deep learning model, LSTM effectively analyzes the sentiment of users forwarding Weibo. These findings serve as an experimental foundation for the efficient integration of Weibo in human-computer interaction education. [ABSTRACT FROM AUTHOR]

It is the basic task of burn therapy to cover the wound with self-healthy skin timely and effectively. However, for patients with extensive burns, autologous skin is usually insufficient, and allogenic or heterogeneous skin leads to strong immune response. It is vital to choose an appropriate treatment for deep extensive burns. Nowadays, the dermal substitute combined with bone marrow mesenchymal stem cells (BM-MSCs) is a prospective strategy for burn wound healing. Denatured acellular dermal matrix (DADM), as one of dermal substitutes, which prepared by burn skin discarded in escharotomy, not only maintains a certain degree of 3D structure of collagen, but also has good biocompatibility. In this study, the preparation method of DADM was improved and DADM was seeded with BM-MSCs. Then BM-MSCs-seeded DADM (DADM/MSCs) was implanted into mice cutaneous wound, and the effect of DADM/MSCs dermal substitute was assessed on skin regeneration. As a result, BM-MSCs survived well and DADM/MSCs scaffolds significantly promoted wound healing in terms of angiogenesis, re-epithelialization and skin appendage regeneration. DADM/MSCs scaffold may represent an alternative promising therapy for wound healing in deep extensive burns. [ABSTRACT FROM AUTHOR]

Fetal dermal mesenchymal stem cells (FDMSCs), isolated from fetal skin, are serving as a novel MSC candidate with great potential in regenerative medicine. More recently, the paracrine actions, especially MSC-derived exosomes, are being focused on the vital role in MSC-based cellular therapy. This study was to evaluate the therapeutic potential of exosomes secreted by FDMSCs in normal wound healing. First, the in vivo study indicated that FDMSC exosomes could accelerate wound closure in a mouse full-thickness skin wound model. Then, we investigated the role of FDMSC-derived exosomes on adult dermal fibroblast (ADFs). The results demonstrated that FDMSC exosomes could induce the proliferation, migration, and secretion of ADFs. We discovered that after treatment of exosomes, the Notch signaling pathway was activated. Then, we found that in FDMSC exosomes, the ligands of the Notch pathway were undetectable expect for Jagged 1, and the results of Jagged 1 mimic by peptide and knockdown by siRNA suggested that Jagged 1 may lead the activation of the Notch signal in ADFs. Collectively, our findings indicated that the FDMSC exosomes may promote wound healing by activating the ADF cell motility and secretion ability via the Notch signaling pathway, providing new aspects for the therapeutic strategy of FDMSC-derived exosomes for the treatment of skin wounds. [ABSTRACT FROM AUTHOR]

BACKGROUND Mesenchymal stem cells (MSCs) have the potential of self-renewal and multi-differentiation and have a wide application prospect in organ transplantation for the effect of inducing immune tolerance. It has found that interleukin 17 (IL-17) could enhance the inhibition effect of MSCs on T cell proliferation and increase the immunosuppressive effect of MSCs. In this study, we aimed to investigate the effect of IL-17-induced MSCs on allograft survival time after transplantation. MATERIAL AND METHODS BMSCs were characterized by differential staining. The allogenic skin transplantations were performed and the BMSCs pre-treated by IL-17 were injected. To assess the immunosuppressive function of IL-17-induced BMSCs, the morphology of the grafts, the homing ability of the BMSCs, and the survival time of the grafts were analyzed. RESULTS BMSCs from BALB/c have multidirectional differentiation potential to differentiate into osteogenic, chondrogenic, and adipogenic lineage cells. IL-17-induced BMSCs prolonged the survival time of allogeneic skin grafts dramatically. We found that there were more labeled MSCs in the skin grafts, and the Treg subpopulations percentage, IL-10, and TGF-β were significantly increased, while the IFN-γ level was decreased compared to the control group and MSCs group. In conclusion, IL-17 can enhance the homing ability of MSCs and regulate the immunosuppressive function of MSC. CONCLUSIONS Our data demonstrate that IL-17 plays the crucial role in MSC homing behaviors and promotes immunosuppression of MSCs during transplantation procedures, suggesting that IL-17-pre-treated MSCs have potential to prolong graft survival and reduce transplant rejection.

Background: Keloid is one kind of benign skin disease caused by hyperplasia of fibroblasts and collagen fibrils. It is refractory due to the lack of an effective treatment at present, which puts pressure on seeking a new therapeutic regimen. Mesenchymal stem cells (MSCs) from fetal skin are considered to play a crucial role in scarless healing. Nevertheless, the efficacy of them in keloid disorders remains poorly understood., Methods: Keloid fibroblasts (KFs), human adult dermal fibroblasts (ADFs), and human fetal dermal mesenchymal stem cells (FDMSCs) were isolated to single cells and cultured in Dulbecco's modified Eagle's medium (DMEM). ADFs and FDMSCs were used to generate ADF-conditioned medium (A-CM) and FDMSC-conditioned medium (F-CM). The effects of A-CM and F-CM on KFs were tested using MTT assay, BrdU assay, TUNEL assay, quantitative polymerase chain reaction, Western blot, and annexin V-FITC/PI binding assay,., Results: FDMSCs inhibited the bioactivity of KFs, downregulated the expression of the antiapoptotic protein BCL-2, and upregulated the expression of the proapoptotic protein BAX of KFs by secreting some soluble substances, thus accelerating the apoptosis of KFs., Conclusion: F-CM induces apoptosis of KFs, providing a novel treatment strategy for keloid disorders.

Purpose: To investigate the relationship between coagulation function and prognosis of non-small cell lung cancer (NSCLC) patients., Methods: 539 patients who were admitted to our hospital for the first time from December 2008 to December 2013 and pathologically diagnosed as NSCLC were enrolled in this study (study group), while 80 healthy persons served as controls (control group). Morning fasting venous blood samples were collected for coagulation function indexes, such as prothrombin time (PT), prothrombin time activity (PTA), international normalized ratio (INR), activated partial thromboplastin time (APTT), fibrinogen (Fib), D-dimer (D-D) and platelet count (PLT) and the coagulation function and survival rate were compared., Results: All coagulation function indexes (PT, PTA, INR, APTT, Fib, D-D and PLT) in the study group patients were significantly different compared with the control group. PTA and APTT in the control group were longer compared with the study group, and PT in the study group was significantly longer compared with control group. No obvious correlation between age and the coagulation function indexes was found. Gender correlated significantly to PT, PTA, INR and APTT. Fib and PLT levels in stage I-II NSCLC patients were significantly higher than those in stage III-IV NSCLC patients. Fib level increased, PT and INR were prolonged and PTA declined significantly and patient survival rate was significantly reduced., Conclusion: Most NSCLC patients have abnormal coagulation function, and each coagulation index may be used to judge the prognosis as well as survival of such patients.

The aim of the study was to investigate the clinical effects of microinvasive video-assisted thoracoscopic surgery (VATS) combined with mechanical ventilation in the treatment of acute respiratory distress syndrome (ARDS) secondary to severe chest trauma. A total of 62 patients with ARDS secondary to severe chest trauma were divided into the observation and control groups. The patients in the observation groups were treated with VATS combined with early mechanical ventilation while patients in the control group were treated using routine open thoracotomy combined with early mechanical ventilation. Compared to the controls, the survival rate of the observation group was significantly higher. The average operation time of the observation group was significantly shorter than that of the control group, and the incidence of complications in the perioperative period of the observation group was significantly lower than that of the control group (p<0.05). The average application time of the observation group was significantly shorter than that of the control group, and the incidence of ventilator-associated complications was significantly lower than that of the control group (p<0.05). In conclusion, a reasonable understanding of the indications and contraindications of VATS, combined with early mechanical treatment significantly improved the success rate of the treatment of ARDS patients secondary to severe chest trauma and reduced the complications.