Technology and Health Care - Volume 32, issue 6

Authors: Wang, Kai | Zhu, Dongming | Chang, Zimin | Wu, Zhiyong

Article Type: Research Article

Abstract: BACKGROUND: The Ultimate Fighting Championship (UFC) stands as a prominent global platform for professional mixed martial arts, captivating audiences worldwide. With its continuous growth and globalization efforts, UFC events have garnered significant attention and achieved commendable results. However, as the scale of development expands, the operational demands on UFC events intensify. At its core, UFC thrives on the exceptional performances of its athletes, which serve as the primary allure for audiences. OBJECTIVE: This study aims to enhance the allure of UFC matches and cultivate exceptional athletes by predicting athlete performance on the field. To achieve this, …a recurrent neural network prediction model based on Bidirectional Long Short-Term Memory (BiLSTM) is proposed. The model seeks to leverage athlete portraits and characteristics for performance prediction. METHODS: The proposed methodology involves constructing athlete portraits and analyzing athlete characteristics to develop the prediction model. The BiLSTM-based recurrent neural network is utilized for its ability to capture temporal dependencies in sequential data. The model’s performance is assessed through experimental analysis. RESULTS: Experimental results demonstrate that the athlete performance prediction model achieved an overall accuracy of 0.7524. Comparative analysis reveals that the proposed BiLSTM model outperforms traditional methods such as Linear Regression and Multilayer Perceptron (MLP), showcasing superior prediction accuracy. CONCLUSION: This study introduces a novel approach to predicting athlete performance in UFC matches using a BiLSTM-based recurrent neural network. By leveraging athlete portraits and characteristics, the proposed model offers improved accuracy compared to classical methods. Enhancing the predictive capabilities in UFC not only enriches the viewing experience but also contributes to the development of exceptional athletes in the sport. Show more

Keywords: Recurrent neural network, UFC, athlete performance, winning percentage forecast, evaluation algorithm, deep learning, BiLSTM, XGBoost

DOI: 10.3233/THC-232000

Citation: Technology and Health Care, vol. 32, no. 6, pp. 4869-4882, 2024

Authors: Sun, Xiaolan | Diao, Yanyan | Si, Fengxia | Yu, Aixia

Article Type: Research Article

Abstract: BACKGROUND: In the contemporary healthcare environment, optimizing patient care strategies is of importance, particularly in neurosurgical environments. While traditional nursing methods have the foundation of patient care, there exists a growing recognition of the potential benefits of comprehensive nurse management. Despite this acknowledgment, there remains a gap in understanding the comparative effectiveness of comprehensive nurse management versus traditional approaches in reducing postoperative psychological stress, enhancing patient satisfaction, and promoting adherence in neurosurgical patients. OBJECTIVE: This study compares the efficacy of comprehensive nurse management against traditional methods in facilitating the postoperative recovery of neurosurgical patients. …METHODS: Taking the traditional nursing management and detailed nursing management of neurosurgical patients in a municipal neurosurgical hospital from March 2021 to March 2022 as an example, the neurosurgery was divided into 50 patients in the detailed nursing management group and 50 patients in the traditional nursing management group. In the clear nursing management group, there were 50 patients, 20 male patients, with an average age of 58.7 ± 3.8 years, and 30 female patients, with an average age of 60.4 ± 4.3 years; In the traditional nursing management group, there were 50 patients, 26 male patients, with an average age of 59.7 ± 3.7 years, and 24 female patients, with an average age of 59.4 ± 3.9 years; Among the 100 patients, there were 60 cases of cerebral infarction, 25 cases of intracerebral hemorrhage and 15 cases of other neurosurgical diseases. RESULTS: Hundred neurosurgical patients were divided into two groups: comprehensive nursing management group and traditional nursing management group. The results showed that the comprehensive treatment effect of patients with detailed nursing management was better than that of the routine nursing group. At the same time, the complications were reduced, and the patient’s satisfaction was higher. CONCLUSION: Through retrospective analysis and investigation of patients, this paper discusses the clinical application of a detailed nursing management model in neurosurgery, which can reduce the probability of infection and other complications and improve the quality of life and treatment effect of patients. Show more

Keywords: Detailed nursing management intervention, neurosurgery, quality of life, cerebrovascular diseases, treatment effect

DOI: 10.3233/THC-232010

Citation: Technology and Health Care, vol. 32, no. 6, pp. 4883-4894, 2024

Authors: Chen, Pan | Wang, Xiaojie | Yan, Pijun | Jiang, Chunxia | Lei, Yi | Miao, Ying

Article Type: Research Article

Abstract: BACKGROUND: Dysfunctions in metabolism and endocrine systems are outcomes of disruptions in human physiological processes, often leading to disease onset. External factors can hinder the human body’s innate capacity for self-regulation and healing, particularly when immune responses are compromised, allowing these factors to interfere with normal bodily functions directly. OBJECTIVE: To explore the effect of uric acid expression water in blood on the occurrence of atrial fibrillation in patients with hyperthyroidism, the expression level of uric acid in the blood and other physiological indexes were compared between patients with no symptoms of atrial fibrillation and patients …with hyperthyroidism with symptoms of atrial fibrillation, to find the correlation between them. METHODS: A group of 112 hyperthyroidism patients who were admitted to our hospital from September 2019 to March 2020 were chosen and split into two groups. The control group consisted of 56 individuals (21 men and 35 women) aged between 16 and 86 years old, with an average age of 46.23 years (± 7.63). The observation group consisted of 56 individuals (24 males and 32 females) between 15 and 79 years, with an average age of 53.44 years (± 8.91). RESULTS: In the patients who were not treated with drugs before hospitalization the disease course and symptoms varied. The patients’ clinical medical and demographic data were recorded and the patients’ physiological indexes were obtained through blood tests and analysis. The differences between the two groups were analyzed by renal function, blood lipid index, thyroid function, and cardiac ultrasound, and these influencing factors were analyzed by regression analysis. The research adhered to ethical norms and ensured clear data presentation by using a rigorous technique to compare uric acid levels and physiological indicators among various patient groups. CONCLUSION: The study concentrated on the validation, repeatability, and contextual interpretation of data to provide a robust and rigorously scientific comparison. The most common is the increase of uric acid in the blood, which can induce other diseases, and atrial fibrillation is one of the most common diseases of cardiovascular diseases. Show more

Keywords: Uric acid level, serum, atrial fibrillation, hyperthyroidism, endocrine

DOI: 10.3233/THC-232028

Citation: Technology and Health Care, vol. 32, no. 6, pp. 4895-4907, 2024

Authors: Zhou, Ying | Li, Chunmei | Chen, Mingming | Gao, Congying

Article Type: Research Article

Abstract: BACKGROUND: Inflammatory bowel disease (IBD), including Crohn’s disease and ulcerative colitis, is characterized by chronic recurrent intestinal inflammation, and its primary clinical manifestations are abdominal pain, diarrhea, hematochezia, etc., which seriously affects patients’ quality of life. OBJECTIVE: To explore the impact of continuing empowerment education based on Roy’s adaptation theory on disease uncertainty and self-management ability in patients with inflammatory bowel disease. METHODS: Sixty patients with inflammatory bowel disease admitted to the hospital from March 2022 to March 2023 were selected and randomly divided into an intervention group (n = …30) and a control group (n = 30). The intervention group received continuous care based on multidisciplinary Cooperation on the WeChat platform, while the control group received routine constant care. The disease uncertainty, hope level, self-care ability, nursing quality, and nursing satisfaction of two groups of patients were compared. RESULT: Both patient groups had lower levels of ambiguity and complexity three months following discharge, with the intervention group exhibiting the lowest levels. On the other hand, the intervention group scored higher on sustaining close connections, taking good action, and having an attitude both now and in the future. The intervention group showed greater health awareness, self-concept, self-care competence, and self-care responsibility ratings. The intervention group also showed more significant attitude, pragmatism, thoroughness, and professionalism in their services. CONCLUSION: Continuous empowerment education based on Roy’s adaptation theory is applied to patients with inflammatory bowel disease. It can enhance confidence, self-management ability, quality of life, and patient satisfaction. Show more

Keywords: Multidisciplinary cooperation, continuous care, inflammatory bowel disease, quality of life

DOI: 10.3233/THC-232032

Citation: Technology and Health Care, vol. 32, no. 6, pp. 4909-4918, 2024

Authors: Liang, Han | Li, Hao | Xia, Nan | Chen, Jingjing | Gao, Linlin | Liu, Hao | Lyu, Ping | Guo, Xiaolin | Yang, Ziwei

Article Type: Research Article

Abstract: BACKGROUND: Long noncoding RNAs (lncRNAs) participate in diseases, especially tumorigenesis, including gastric cancer (GC). Although lncRNAs in GC tissues have been extensively studied in previous research, the possible significance of circulating lncRNAs in diagnosing GC is still unknown. OBJECTIVE: The present work investigated lncRNAs ZFPM2-AS1 and XIST with high expression in GC tissues proved as potential plasma biomarkers from 20 early GC cases, 100 GC cases, and 90 normal subjects. METHODS: The possible correlation between ZFPM2-AS1 and XIST expression levels was analyzed with general characteristics and clinicopathological features. The performance in diagnosis was …assessed according to receiver operating characteristic (ROC) analysis. RESULTS: According to the results, XIST and ZFPM2-AS1 expression remarkably increased within GC plasma relative to normal subjects (P < 0.01); besides, lncRNA XIST expression after surgery had a tendency of downregulation compared with preoperative levels (P < 0.05). Moreover, the area under ROC curve (AUC) values were 0.62 for ZFPM2-AS1 and 0.68 for XIST, while the pooled AUC value of CA-724 and two lncRNAs was 0.751. CONCLUSION: Circulating lncRNAs ZFPM2-AS1 and XIST can serve as the candidate plasma biomarkers used to diagnose GC. Show more

Keywords: Long noncoding RNA, gastric cancer, ZFPM2-AS1, XIST, diagnosis, plasma, biomarker

DOI: 10.3233/THC-232033

Citation: Technology and Health Care, vol. 32, no. 6, pp. 4919-4928, 2024

Authors: Zhong, Fengxing | Yin, Xiuping | Liu, Xinxin | Zhang, Qiming

Article Type: Research Article

Abstract: BACKGROUND: Understanding how pharmaceutical formulas target specific illnesses is crucial for developing effective treatments. Enriching ion channel data is a critical first step in comprehending a formula’s mechanism of action. OBJECTIVE: This study aims to explore the effective disease spectrum of the Qi Yu granule formula through network pharmacology analysis and backtracking, and analyze its potential curative effects on liver and spleen system diseases, particularly depression and breast cancer. METHODS: Using pharmacological tools and database analysis, the ion channel data of the formula’s components were investigated. The effective disease spectrum was determined, and …diseases related to liver and gallbladder, liver depression, and spleen deficiency were identified. Network pharmacology analysis was conducted to backtrack diseases, target gene proteins, and drug compositions. The extraction technology of volatile oil from medicinal herbs was experimentally studied to optimize the preparation process. RESULTS: The effective disease spectrum analysis identified potential curative effects of the Qi Yu granule formula on various diseases, including breast cancer. Backtracking revealed relationships between diseases, target gene proteins, and drug compositions. Experimental studies on volatile oil extraction provided insights into optimizing the preparation process. CONCLUSION: The study underscores the potential therapeutic benefits of the Qi Yu granule formula for liver and spleen system diseases. By integrating network pharmacology analysis and experimental research, this study offers valuable insights into the formulation and efficacy of the Qi Yu granules, paving the way for further exploration and optimization of TCM formulations. Show more

Keywords: Qi Yu granules, liver stagnation, edible plants, network pharmacology, spleen deficiency syndrome

DOI: 10.3233/THC-232034

Citation: Technology and Health Care, vol. 32, no. 6, pp. 4929-4946, 2024

Authors: Wu, Xiaoqian | Chen, Cheng | Quan, Lili

Article Type: Research Article

Abstract: BACKGROUND: Traditional methods have the limitations of low accuracy and inconvenient operation in analyzing students’ abnormal behavior. Hence, a more intuitive, flexible, and user-friendly visualization tool is needed to help better understand students’ behavior data. OBJECTIVE: In this study a visual analysis and interactive interface of students’ abnormal behavior based on a clustering algorithm were examined and designed. METHODS: Firstly, this paper discusses the development of traditional methods for analyzing students’ abnormal behavior and visualization technology and discusses its limitations. Then, the K-means clustering algorithm is selected as the solution to find potential …abnormal patterns and groups from students’ behaviors. By collecting a large number of students’ behavior data and preprocessing them to extract relevant features, a K-means clustering algorithm is applied to cluster the data and obtain the clustering results of students’ abnormal behaviors. To visually display the clustering results and help users analyze students’ abnormal behaviors, a visual analysis method and an interactive interface are designed to present the clustering results to users. The interactive functions are provided, such as screening, zooming in and out, and correlation analysis, to support users’ in-depth exploration and analysis of data. Finally, the experimental evaluation is carried out, and the effectiveness and practicability of the proposed method are verified by using big data to obtain real student behavior data. RESULTS: The experimental results show that this method can accurately detect and visualize students’ abnormal behaviors and provide intuitive analysis results. CONCLUSION: This paper makes full use of the advantages of big data to understand students’ behavior patterns more comprehensively and provides a new solution for students’ management and behavior analysis in the field of education. Future research can further expand and improve this method to adapt to more complex students’ behavior data and needs. Show more

Keywords: Clustering algorithm, student behavior, big data, visual analysis, interactive interface

DOI: 10.3233/THC-232054

Citation: Technology and Health Care, vol. 32, no. 6, pp. 4947-4963, 2024

Authors: Wang, Jing | Yin, Liang

Article Type: Research Article

Abstract: BACKGROUND: More than a million people are affected by brain tumors each year; high-grade gliomas (HGGs) and low-grade gliomas (LGGs) present serious diagnostic and treatment hurdles, resulting in shortened life expectancies. Glioma segmentation is still a significant difficulty in clinical settings, despite improvements in Magnetic Resonance Imaging (MRI) and diagnostic tools. Convolutional neural networks (CNNs) have seen recent advancements that offer promise for increasing segmentation accuracy, addressing the pressing need for improved diagnostic and therapeutic approaches. OBJECTIVE: The study intended to develop an automated glioma segmentation algorithm using CNN to accurately identify tumor components in MRI …images. The goal was to match the accuracy of experienced radiologists with commercial instruments, hence improving diagnostic precision and quantification. METHODS: 285 MRI scans of high-grade gliomas (HGGs) and low-grade gliomas (LGGs) were analyzed in the study. T1-weighted sequences were utilised for segmentation both pre-and post-contrast agent administration, along with T2-weighted sequences (with and without Fluid Attenuation by Inversion Recovery [FAIRE]). The segmentation performance was assessed with a U-Net network, renowned for its efficacy in medical image segmentation. DICE coefficients were computed for the tumour core with contrast enhancement, the entire tumour, and the tumour nucleus without contrast enhancement. RESULTS: The U-Net network produced DICE values of 0.7331 for the tumour core with contrast enhancement, 0.8624 for the total tumour, and 0.7267 for the tumour nucleus without contrast enhancement. The results align with previous studies, demonstrating segmentation accuracy on par with professional radiologists and commercially accessible segmentation tools. CONCLUSION: The study developed a CNN-based automated segmentation system for gliomas, achieving high accuracy in recognising glioma components in MRI images. The results confirm the ability of CNNs to enhance the accuracy of brain tumour diagnoses, suggesting a promising avenue for future research in medical imaging and diagnostics. This advancement is expected to improve diagnostic processes for clinicians and patients by providing more precise and quantitative results. Show more

Keywords: Biomedical imaging, CNN, deep learning, glioma, neuroimages, MRI

DOI: 10.3233/THC-240158

Citation: Technology and Health Care, vol. 32, no. 6, pp. 4965-4982, 2024

Authors: Wen, Yi | Li, Xinyan | Shu, Wan | Zhang, Hong | Shen, Zhefan | Huang, Zhaoxia

Article Type: Review Article

Abstract: BACKGROUND: About 186 million people in the world suffer from infertility, and there is one infertile couple in every 4–6 couples. It is thus essential to find effective psychological treatment. OBJECTIVE: To conduct a systematic review of previous meta-analyses on mindfulness-based therapy outcomes in infertile female patients and a meta-analysis of studies nested within these meta-analyses. METHODS: Randomized controlled trials (RCTS) on the efficacy of mindset-based interventions in infertile female patients were retrieved from PubMed, The Cochrane Library, Embase, Web of Science, CNI, VIP Database, and Wanfang Database until March 1, 2023. Two …researchers screened the literature, extracted data according to inclusion and exclusion criteria, and conducted quality control according to Cochrane Handbook 5.1.0. When there was ambiguity, a third party determined it. The meta-analysis was performed using RevMan 5.3 software. RESULT: 14 randomized controlled trials involving 1784 patients were included. Meta-analysis showed that compared with conventional care, mindfulness-based intervention can effectively relieve anxiety in female infertility patients [SMD = - 2.25, 95% CI (- 2.90, - 1.60), P < 0.00001], depression [SMD = - 2.25, 95% CI (- 2.99, - 1.52), P < 0.00001], perceived stress [SMD = - 0.99, 95% CI (- 1.27, - 0.71), P < 0.00001], improved quality of life, physiological function [MD = 14.03, 95% CI (11.98, 16.07), P < 0.00001], Role limitations due to physical problems [MD = 11.30, 95% CI (5.71, 16.90), P < 0.0001], vitality [MD = 11.55, 95% CI (9.46, 13.65), P < 0.00001], mental health [MD = 17.32, 95% CI (15.29, 19.35), P < 0.00001]. CONCLUSION: Existing evidence shows that mindfulness therapy can effectively relieve the anxiety and depression of infertile women, reduce the level of stress, and improve the quality of life and sleep quality. However, due to the limited quantity and quality of the literature, multi-center, large-sample, and high-quality randomized controlled studies should be conducted in the future. Show more

Keywords: Mindfulness-based therapy, infertility, women, meta-analysis, evidence-based nursing, randomized controlled trial (RCTS), RF dimension

DOI: 10.3233/THC-240174

Citation: Technology and Health Care, vol. 32, no. 6, pp. 4983-4997, 2024

Authors: Zhi, Jin | Li, Zhao

Article Type: Research Article

Abstract: BACKGROUND: Cerebral infarction is a health problem of global concern and brings a particular burden to medical treatment. OBJECTIVE: To analyze the correlation between insulin resistance (IR) levels and changes in cerebral atherosclerosis (AS) degree in non-diabetic patients with cerebral infarction. METHODS: A total of 134 non-diabetic patients with cerebral infarction who visited the Department of Neurology of our hospital from May 2019 to October 2020 were selected and underwent MRA/CTA (Magnetic resonance angiography/Computed tomography angiography) of cerebral arteries to refine the cerebrovascular imaging data, and according to the results of cerebral AS …load, the patients were divided into mild AS group and severe AS group, and the insulin resistance index was calculated with HOMA-IR (homeostasis model assessment of insulin resistance) to evaluate the IR level and HOMA-IR was compared between the two groups. Spearman correlation was used to analyze the correlation between the levels of IR in patients and the changes in cerebral AS load. RESULTS: 54 individuals had severe AS and 80 patients had mild AS, according to an MRA/CTA of the cerebral arteries. There was a significant difference (P < 0.05) in HOMA-IR between the difficult and gentle AS groups. A significant link between HOMA-IR and the severity of cerebral AS in patients was found using Spearman correlation analysis (r = 0.850, P < 0.05). CONCLUSION: The IR phenomenon was prevalent in non-diabetic patients with cerebral infarction, and the level of IR was closely related to the severity of cerebral AS. Show more

Keywords: Non-diabetic cerebral infarction, insulin resistance, Cerebral AS, relevance, metabolic syndrom

DOI: 10.3233/THC-240179

Citation: Technology and Health Care, vol. 32, no. 6, pp. 4999-5007, 2024