Technology and Health Care - Volume 32, issue 6

Authors: Alsaleh, Hadeel

Article Type: Research Article

Abstract: BACKGROUND: Schwann cell sheaths are the source of benign, slowly expanding tumours known as acoustic neuromas (AN). The diagnostic and treatment approaches for AN must be patient-centered, taking into account unique factors and preferences. OBJECTIVE: The purpose of this study is to investigate how machine learning and artificial intelligence (AI) can revolutionise AN management and diagnostic procedures. METHODS: A thorough systematic review that included peer-reviewed material from public databases was carried out. Publications on AN, AI, and deep learning up until December 2023 were included in the review’s purview. RESULTS: …Based on our analysis, AI models for volume estimation, segmentation, tumour type differentiation, and separation from healthy tissues have been developed successfully. Developments in computational biology imply that AI can be used effectively in a variety of fields, including quality of life evaluations, monitoring, robotic-assisted surgery, feature extraction, radiomics, image analysis, clinical decision support systems, and treatment planning. CONCLUSION: For better AN diagnosis and treatment, a variety of imaging modalities require the development of strong, flexible AI models that can handle heterogeneous imaging data. Subsequent investigations ought to concentrate on reproducing findings in order to standardise AI approaches, which could transform their use in medical environments. Show more

Keywords: Artificial intelligence, diagnosis, acoustic neuroma, impact, management

DOI: 10.3233/THC-232043

Citation: Technology and Health Care, vol. 32, no. 6, pp. 3801-3813, 2024

Authors: Wu, Qian | Zang, Ruiqi | Zhang, Yong

Article Type: Research Article

Abstract: BACKGROUND: Pregnancy is an important process in women’s life, which is widely concerned by women. In recent years, the incidence of premature delivery (PTD) becomes more and more higher due to the development of auxiliary reproduction and ovulation induction technologies and the changes of pregnant women’s lifestyle and physical quality. PTD not only affects postpartum recovery and causes great physical pains, but it also has adverse effects on the birth state of neonates and even leads to neonatal death OBJECTIVE: The predictive values of cervix length (CL) measurement based on transvaginal ultrasonography (TVUS) and pathological examination …of placenta for premature delivery (PTD) were investigated and the correlation between PTD and infection was analyzed. METHODS: 120 pregnant women with PTD or high-risk factors for PTD admitted to The Affiliated Hospital of Southwest Medical University between February 2020 and March 2022 were included as the subjects and underwent pathological examination of placenta and TVUS for CL measurement. The final gestational age was set as the standard for the evaluation on the predictive values of pathological examination of placenta and TVUS. What’s more, 36 subjects in PTD group and 84 in normal delivery group (control group) underwent pathological examination of placenta for the analysis of the correlation between PTD and infection. RESULTS: The joint inspection method showed significantly better sensitivity, specificity, PPV, and NPV compared to single CL or pathological examination of the placenta (P < 0.05). Among pregnant women, those with CL ⩽ 30 mm and positive placental pathology had a higher proportion compared to those with CL > 30 mm and negative placental pathology (P < 0.05). Furthermore, the incidence of Ureaplasma Urealyticum (UU), Chlamydia Trachomatis (CT), and Chorioamnionitis (CA) in vaginal discharge of the preterm delivery (PTD) group was significantly higher than that of the control group (P < 0.05). CONCLUSION: The combination of CL ⩽ 30 mm and positive placental pathology could effectively predict PTD and placental infection was notably correlated with the occurrence of PTD. Show more

Keywords: Transvaginal ultrasonography, cervix length, pathological examination of placenta, premature delivery, infection

DOI: 10.3233/THC-230079

Citation: Technology and Health Care, vol. 32, no. 6, pp. 3815-3827, 2024

Authors: MA, Sreema | A, Jayachandran | Perumal T, Sudarson Rama

Article Type: Research Article

Abstract: BACKGROUND: Segmentation of retinal fragments like blood vessels, Optic Disc (OD), and Optic Cup (OC) enables the early detection of different retinal pathologies like Diabetic Retinopathy (DR), Glaucoma, etc. OBJECTIVE: Accurate segmentation of OD remains challenging due to blurred boundaries, vessel occlusion, and other distractions and limitations. These days, deep learning is rapidly progressing in the segmentation of image pixels, and a number of network models have been proposed for end-to-end image segmentation. However, there are still certain limitations, such as limited ability to represent context, inadequate feature processing, limited receptive field, etc., which lead to …the loss of local details and blurred boundaries. METHODS: A multi-dimensional dense attention network, or MDDA-Net, is proposed for pixel-wise segmentation of OD in retinal images in order to address the aforementioned issues and produce more thorough and accurate segmentation results. In order to acquire powerful contexts when faced with limited context representation capabilities, a dense attention block is recommended. A triple-attention (TA) block is introduced in order to better extract the relationship between pixels and obtain more comprehensive information, with the goal of addressing the insufficient feature processing. In the meantime, a multi-scale context fusion (MCF) is suggested for acquiring the multi-scale contexts through context improvement. RESULTS: Specifically, we provide a thorough assessment of the suggested approach on three difficult datasets. In the MESSIDOR and ORIGA data sets, the suggested MDDA-NET approach obtains accuracy levels of 99.28% and 98.95%, respectively. CONCLUSION: The experimental results show that the MDDA-Net can obtain better performance than state-of-the-art deep learning models under the same environmental conditions. Show more

Keywords: Deep learning, dense prediction networks, fundus images, segmentation

DOI: 10.3233/THC-230310

Citation: Technology and Health Care, vol. 32, no. 6, pp. 3829-3846, 2024

Authors: Mujahid, Muhammad | Rustam, Furqan | Chakrabarti, Prasun | Mallampati, Bhargav | de la Torre Diez, Isabel | Gali, Pradeep | Chunduri, Venkata | Ashraf, Imran

Article Type: Research Article

Abstract: Pneumonia is a dangerous disease that kills millions of children and elderly patients worldwide every year. The detection of pneumonia from a chest x-ray is perpetrated by expert radiologists. The chest x-ray is cheaper and is most often used to diagnose pneumonia. However, chest x-ray-based diagnosis requires expert radiologists which is time-consuming and laborious. Moreover, COVID-19 and pneumonia have similar symptoms which leads to false positives. Machine learning-based solutions have been proposed for the automatic prediction of pneumonia from chest X-rays, however, such approaches lack robustness and high accuracy due to data imbalance and generalization errors. This study focuses on …elevating the performance of machine learning models by dealing with data imbalanced problems using data augmentation. Contrary to traditional machine learning models that required hand-crafted features, this study uses transfer learning for automatic feature extraction using Xception and VGG-16 to train classifiers like support vector machine, logistic regression, K nearest neighbor, stochastic gradient descent, extra tree classifier, and gradient boosting machine. Experiments involve the use of hand-crafted features, as well as, transfer learning-based feature extraction for pneumonia detection. Performance comparison using Xception and VGG-16 features suggest that transfer learning-based features tend to show better performance than hand-crafted features and an accuracy of 99.23% can be obtained for pneumonia using chest X-rays. Show more

Keywords: Pneumonia prediction, COVID-19, transfer learning, automatic feature extraction, chest radiographs

DOI: 10.3233/THC-230313

Citation: Technology and Health Care, vol. 32, no. 6, pp. 3847-3870, 2024

Authors: Ping, Yuxia

Article Type: Research Article

Abstract: BACKGROUND: In recent years, artificial intelligence (AI) technology has been continuously advancing and finding extensive applications, with one of its core technologies, machine learning, being increasingly utilized in the field of healthcare. OBJECTIVE: This research aims to explore the role of Artificial Intelligence (AI) technology in psychological counseling and utilize machine learning algorithms to predict counseling outcomes. METHODS: Firstly, by employing natural language processing techniques to analyze user conversations with AI chatbots, researchers can gain insights into the psychological states and needs of users during the counseling process. This involves detailed analysis using …text analysis, sentiment analysis, and other relevant techniques. Subsequently, machine learning algorithms are used to establish predictive models that forecast counseling outcomes and user satisfaction based on data such as user language, emotions, and behavior. These predictive results can assist counselors or AI chatbots in adjusting counseling strategies, thereby enhancing counseling effectiveness and user experience. Additionally, this study explores the potential and prospects of AI technology in the field of psychological counseling. RESULTS: The research findings indicate that the designed machine learning models achieve an accuracy rate of approximately 89% in analyzing psychological conditions. This demonstrates significant innovation and breakthroughs in AI technology. Consequently, AI technology will gradually become a highly important tool and method in the field of psychological counseling. CONCLUSION: In the future, AI chatbots will become more intelligent and personalized, providing users with precise, efficient, and convenient psychological counseling services. The results of this research provide valuable technical insights for further improving AI-supported psychological counseling, contributing positively to the application and development of AI technology. Show more

Keywords: Artificial intelligence, machine learning, natural language, psychological counseling, sentiment analysis

DOI: 10.3233/THC-230809

Citation: Technology and Health Care, vol. 32, no. 6, pp. 3871-3888, 2024

Authors: Chen, Xiaoqun | Song, Yingliang

Article Type: Research Article

Abstract: BACKGROUND: Matrine has been reported inhibitory effects on ovarian cancer (OC) cell progression, development, and apoptosis. However, the molecular targets of matrine against OC and the underlying mechanisms of action remain elusive. OBJECTIVE: This study endeavors to unveil the potential targets of matrine against OC and to explore the intricate relationships between these targets and the pathogenesis of OC. METHODS: The effects of matrine on the OC cells (A2780 and AKOV3) viability, apoptosis, migration, and invasion was investigated through CCK-8, flow cytometry, wound healing, and Transwell analyses, respectively. Next, Matrine-related targets, OC-related genes, …and ribonucleic acid (RNA) sequence data were harnessed from publicly available databases. Differentially expressed analyses, protein-protein interaction (PPI) network, and Venn diagram were involved to unravel the core targets of matrine against OC. Leveraging the GEPIA database, we further validated the expression levels of these core targets between OC cases and controls. Mendelian randomization (MR) study was implemented to delve into potential causal associations between core targets and OC. The AutoDock software was used for molecular docking, and its results were further validated using RT-qPCR in OC cell lines. RESULTS: Matrine reduced the cell viability, migration, invasion and increased the cell apoptosis of A2780 and AKOV3 cells (P < 0.01). A PPI network with 578 interactions among 105 candidate targets was developed. Finally, six core targets (TP53, CCND1, STAT3, LI1B, VEGFA, and CCL2) were derived, among which five core targets (TP53, CCND1, LI1B, VEGFA, and CCL2) differential expressed in OC and control samples were further picked for MR analysis. The results revealed that CCND1 and TP53 were risk factors for OC. Molecular docking analysis demonstrated that matrine had good potential to bind to TP53, CCND1, and IL1B. Moreover, matrine reduced the expression of CCND1 and IL1B while elevating P53 expression in OC cell lines. CONCLUSIONS: We identified six matrine-related targets against OC, offering novel insights into the molecular mechanisms underlying the therapeutic effects of matrine against OC. These findings provide valuable guidance for developing more efficient and targeted therapeutic approaches for treating OC. Show more

Keywords: Ovarian cancer, Matrine, Mendelian randomization, target, molecular docking

DOI: 10.3233/THC-231051

Citation: Technology and Health Care, vol. 32, no. 6, pp. 3889-3902, 2024

Authors: Gao, Wenlong | Zeng, Zhimei | Ma, Xiaojie | Ke, Yongsong | Zhi, Minqian

Article Type: Research Article

Abstract: BACKGROUND: The morbidity and mortality of heart disease are increasing in middle-aged and elderly people in China. It is necessary to explore relationships and interactive associations between heart disease and its risk factors in order to prevent heart disease. OBJECTIVE: To establish a Bayesian network model of heart disease and its influencing factors in middle-aged and elderly people in China, and explore the applicability of the elite-based structure learner using genetic algorithm based on ensemble learning (EN-ESL-GA) algorithm in etiology analysis and disease prediction. METHODS: Based on the 2013 national tracking survey data …from China Health and Retirement Longitudinal Study (CHARLS) database, EN-ESL-GA algorithm was used to learn the Bayesian network structure. Then we input the data and the learned network structure into the Netica software for parameter learning and inference analysis. RESULTS: The Bayesian network model based on the EN-ESL-GAalgorithm can effectively excavate the complex network relationships and interactive associations between heart disease and its risk factors in middle-aged and elderly people in China. CONCLUSIONS: The Bayesian network model based on the EN-ESL-GA algorithm has good applicability and application prospect in the prediction of diseases prevalence risk. Show more

Keywords: Bayesian networks, heart disease, influence factors, middle-aged and elderly people

DOI: 10.3233/THC-231215

Citation: Technology and Health Care, vol. 32, no. 6, pp. 3903-3912, 2024

Authors: Leinum, Lisbeth R. | Baandrup, Anders O. | Gögenur, Ismail | Krogsgaard, Marianne | Azawi, Nessn

Article Type: Research Article

Abstract: BACKGROUND: Innovations in healthcare technologies have the potential to address challenges, including the monitoring of fluid balance. OBJECTIVE: This study aims to evaluate the functionality and accuracy of a digital technology compared to standard manual documentation in a real-life setting. METHODS: The digital technology, LICENSE, was designed to calculate fluid balance using data collected from devices measuring urine, oral and intravenous fluids. Participating patients were connected to the LICENSE system, which transmitted data wirelessly to a database. These data were compared to the nursing staff’s manual measurements documented in the electronic patient record …according to their usual practice. RESULTS: We included 55 patients in the Urology Department needing fluid balance charting and observed them for an average of 22.9 hours. We found a mean difference of - 44.2 ml in total fluid balance between the two methods. Differences ranged from - 2230 ml to 2695 ml, with a divergence exceeding 500 ml in 57.4% of cases. The primary source of error was inaccurate or omitted manual documentation. However, errors were also identified in the oral LICENSE device. CONCLUSIONS: When used correctly, the LICENSE system performs satisfactorily in measuring urine and intravenous fluids, although the oral device requires revision due to identified errors. Show more

Keywords: Water-electrolyte balance, monitoring, physiologic, digital technology, automation, equipment design

DOI: 10.3233/THC-231303

Citation: Technology and Health Care, vol. 32, no. 6, pp. 3913-3924, 2024

Authors: Wu, Cuiying | Li, Yunjun | Luo, Yongchun | Dai, Yiwu | Qin, Jiazhen | Liu, Ning | Xu, Ruxiang | Li, Xuezhen | Zhang, Peng

Article Type: Research Article

Abstract: BACKGROUND: Low-grade gliomas (LGG) are a variety of brain tumors that show different clinical outcomes. The methylation of the GSTM5 gene has been noted in the development of LGG, however, its prognostic importance remains uncertain. OBJECTIVE: The objective of this study was to examine the correlation between GSTM5 DNA methylation and clinical outcomes in individuals diagnosed with LGG. METHODS: Analysis of GSTM5 methylation levels in LGG samples was conducted using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. The overall survival based on GSTM5 methylation status was evaluated …using Kaplan-Meier curves. The DNA methylation heatmap for particular CpG sites in the GSTM5 gene was visualized using the “pheatmap” R package. RESULTS: The study analyzed that LGG tumors had higher levels of GSTM5 methylation than normal tissues. There was an inverse relationship discovered between GSTM5 expression and methylation. LGG patients with hypermethylation of GSTM5 promoter experienced a positive outcome. Age, grade, and GSTM5 methylation were determined as independent prognostic factors in LGG through both univariate and multivariate Cox regression analyses. CONCLUSION: Methylation of GSTM5 DNA, specifically at certain CpG sites, is linked to a positive outlook in patients with LGG. Utilizing the “pheatmap” R package to visualize GSTM5 methylation patterns offers important information for identifying prognostic markers and therapeutic targets in low-grade gliomas. Show more

Keywords: Low-grade glioma, glutathione S-transferase mu class 5 (GSTM5), prognosist, methylaion, immune cells

DOI: 10.3233/THC-231316

Citation: Technology and Health Care, vol. 32, no. 6, pp. 3925-3942, 2024

Authors: Yin, Huimin | Yan, Zhanjie | Zhao, Fangcheng

Article Type: Research Article

Abstract: BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is currently an important chronic liver disease threatening human life and health. OBJECTIVE: To investigate the risk factors of hepatocellular carcinoma (HCC) associated with nonalcoholic fatty liver disease (NAFLD) by systematic review. METHODS: We conducted a systematic review and meta-analysis. A systematic search of Chinese and English databases (PubMed, Web of Science, Cochrane Library, China national knowledge infrastructure (CNKI), Wanfang database, and VIP database) was performed until June 30, 2023. Studies were included to investigate the risk factors for HCC in patients with NAFLD. Quality evaluation was …performed using the Newcastle-Ottawa Literature Quality Evaluation Scale, and then hazard ratios (HRs) for different influencing factors were combined. RESULTS: We reviewed the results of 12 high-quality cohort studies involving 738,934 patients with NAFLD and 1,480 developed HCC. A meta-analysis based on a random-effects model showed that advanced age (HR = 1.81, 95% CI: 1.51–2.17), male gender (HR = 2.51, 95% CI: 1.67–3.78), hypertension (HR = 1.87, 95% CI: 1.05–3.33), and diabetes (HR = 2.27, 95% CI: 1.63–3.16) were risk factors for HCC in NAFLD, and the differences were statistically significant. However, there was no statistically significant effect of current smoking (HR = 1.45, 95% CI: 0.72–2.92) and dyslipidemia (HR = 1.03, 95% CI: 0.72–1.47) on HCC incidence in this study. CONCLUSION: Age, sex, hypertension and diabetes are risk factors for HCC in NAFLD patients. Diabetic NAFLD patients have a 2.27-fold increased risk of HCC, and health education and intervention for elderly, male, NAFLD patients with diabetes and hypertension need to be strengthened to promote a reduction in the risk of HCC. Show more

Keywords: Nonalcoholic fatty liver disease, hepatocellular carcinoma, risk factors, meta-analysis

DOI: 10.3233/THC-231331

Citation: Technology and Health Care, vol. 32, no. 6, pp. 3943-3954, 2024