Technology and Health Care最新文献_第8页

Comprehensive lifecycle quality control of medical data - automated monitoring and feedback mechanisms based on artificial intelligence. 医疗数据全生命周期质量控制——基于人工智能的自动监测与反馈机制。

IF 1.4 4区医学

Technology and Health Care Pub Date : 2025-04-16 DOI: 10.1177/09287329251330222

Haixia Liu, Zhanju Li, Zijian Song

{"title":"Comprehensive lifecycle quality control of medical data - automated monitoring and feedback mechanisms based on artificial intelligence.","authors":"Haixia Liu, Zhanju Li, Zijian Song","doi":"10.1177/09287329251330222","DOIUrl":"https://doi.org/10.1177/09287329251330222","url":null,"abstract":"BackgroundDigital healthcare's advance has underscored an urgent requirement for solid medical record quality control, critical for data integrity, surpassing manual methods' inadequacies.ObjectiveThe goal was to develop an AI system to manage medical record quality control comprehensively, using advanced AI like reinforcement learning and NLP to boost management's precision and efficiency.MethodsThis AI system uses a closed-loop framework for real-time record review using natural language processing techniques and reinforcement learning, synchronized with the hospital information system. It features a data layer for monitoring, a service layer for AI analysis, and a presentation layer for user engagement. Its impact was evaluated by comparing quality metrics pre- and post-deployment.ResultsWith the AI system, quality control became fully operational, with review times per record plummeting from 4200 s to 2 s. The share of Grade A records rose from 89.43% to 99.21%, and the system markedly minimized formal and substantive record errors, enhancing completeness and accuracy. The implementation of the artificial intelligence-based medical record quality control system optimizes the quality control process, dynamically regulates the diagnostic behavior of medical staff, and promotes the standardization and normalization of clinical medical record writing.ConclusionsThe AI-driven system significantly upgraded the management of medical records in terms of efficiency and accuracy. It provides a scalable approach for hospitals to refine quality control, propelling healthcare towards heightened intelligence and automation, and foreshadowing AI's pivotal role in future healthcare quality management.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"9287329251330222"},"PeriodicalIF":1.4,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144053463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing the need for biomedical engineering graduate programs in Saudi Arabia: A stakeholder perspective. 评估沙特阿拉伯生物医学工程研究生项目的需求：利益相关者的视角。

IF 1.4 4区医学

Technology and Health Care Pub Date : 2025-04-16 DOI: 10.1177/09287329251330375

Ahmed A Aldohbeyb, Suhail S Alshahrani, Abdulelah S Alrebaish, Abdulaziz K Assaifan, Abdulaziz S Fakhouri, Khalid Alhussaini, Ahmad O Alokaily

{"title":"Assessing the need for biomedical engineering graduate programs in Saudi Arabia: A stakeholder perspective.","authors":"Ahmed A Aldohbeyb, Suhail S Alshahrani, Abdulelah S Alrebaish, Abdulaziz K Assaifan, Abdulaziz S Fakhouri, Khalid Alhussaini, Ahmad O Alokaily","doi":"10.1177/09287329251330375","DOIUrl":"https://doi.org/10.1177/09287329251330375","url":null,"abstract":"BackgroundBiomedical Engineering (BME) plays a crucial role in advancing healthcare. While BME graduate programs have expanded globally, Saudi Arabia faces a significant gap in this area. As the country shifts from being primarily a consumer to a producer in the healthcare sector, determining the essential knowledge and skills required for BME graduates to meet market demands becomes increasingly important.ObjectiveThis study aims to assess the need for a graduate-level BME program in Riyadh and to design a Master's program that aligns with international standards and industry requirements.MethodsA comprehensive questionnaire was developed to evaluate the proposed program's coverage of BME fields, its relevance to current and future job market demands, and stakeholder feedback. The questionnaire was distributed to 45 managerial and executive-level BME professionals involved in hiring and policymaking.ResultsThe findings indicated strong support for the program, with respondents affirming its comprehensiveness and alignment with industry needs. Public sector participants showed greater enthusiasm compared to the private sector, which preferred hiring candidates with existing qualifications. Additionally, 25% of respondents recommended incorporating regulatory and business courses to enhance the curriculum.ConclusionThe results highlight the urgent need for graduate-level BME education in Saudi Arabia to support the country's healthcare objectives and better prepare graduates for the dynamic and evolving job market.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"9287329251330375"},"PeriodicalIF":1.4,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144053448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning for improved medical device management: A focus on dialysis machines. 用于改进医疗设备管理的机器学习：对透析机的关注。

IF 1.4 4区医学

Technology and Health Care Pub Date : 2025-04-16 DOI: 10.1177/09287329251328815

Mato Martinović, Milena Kosović, Lemana Spahić, Adna Softić, Lejla Gurbeta Pokvić, Almir Badnjević

{"title":"Machine learning for improved medical device management: A focus on dialysis machines.","authors":"Mato Martinović, Milena Kosović, Lemana Spahić, Adna Softić, Lejla Gurbeta Pokvić, Almir Badnjević","doi":"10.1177/09287329251328815","DOIUrl":"https://doi.org/10.1177/09287329251328815","url":null,"abstract":"BackgroundDialysis is a very complex treatment that is received by around 3 million people annually. Around 10% of the death cases in the presence of the dialysis machine were due to the technical errors of dialysis devices. One of the ways to maintain dialysis devices is by using machine learning and predictive maintenance in order to reduce the risk of patient's death, costs of repairs and provide a higher quality treatment.ObjectivePrediction of dialysis machine performance status and errors using regression models.MethodThe methodology includes seven steps: data collection, processing, model selection, training, evaluation, fine-tuning, and prediction. After preprocessing 1034 measurements, twelve machine learning models were trained to predict dialysis machine performance, and temperature and conductivity error values.ResultsEach model was trained 100 times on different splits of the dataset (80% training, 10% testing, 10% evaluation). Logistic regression achieved the highest accuracy in predicting dialysis machine performance. For temperature predictions, Lasso regression had the lowest MSE on training data (0.0058), while Linear regression showed the highest R² (0.59). For conductivity predictions, Lasso regression provided the lowest MSE (0.134), with Decision tree achieving the highest R² (0.2036). SVM attained the lowest MSE on testing dataset, with 0.0055 for temperature and 0.1369 for conductivity.ConclusionThe results of this study demonstrate that clinical engineering (CE) and health technology management (HTM) departments in healthcare institutions can benefit from proposed automated systems for advanced management of dialysis machines.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"9287329251328815"},"PeriodicalIF":1.4,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144008662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Overview of SARS-CoV-2 variants in the federation of Bosnia and Herzegovina throughout four waves of the pandemic. 波斯尼亚和黑塞哥维那联邦在四波大流行期间的SARS-CoV-2变体概述。

IF 1.4 4区医学

Technology and Health Care Pub Date : 2025-04-11 DOI: 10.1177/09287329251327020

Ivana Čeko, Naida Mulahuseinović, Selma Durgut, Lana Salihefendić, Adna Ašić, Dino Pećar, Nejira Handžić, Sabina Šegalo, Lejla Lasić, Rijad Konjhodžić

{"title":"Overview of SARS-CoV-2 variants in the federation of Bosnia and Herzegovina throughout four waves of the pandemic.","authors":"Ivana Čeko, Naida Mulahuseinović, Selma Durgut, Lana Salihefendić, Adna Ašić, Dino Pećar, Nejira Handžić, Sabina Šegalo, Lejla Lasić, Rijad Konjhodžić","doi":"10.1177/09287329251327020","DOIUrl":"https://doi.org/10.1177/09287329251327020","url":null,"abstract":"AimCOVID-19 pandemic, caused by SARS-CoV-2, has had a profound impact on global health, including in Bosnia and Herzegovina, which faced unique challenges due to limited testing and high mortality rates. This analysis aimed to identify mutations and detect different SARS-CoV-2 lineages across four pandemic waves.MethodologyA total of 127 SARS-CoV-2 samples were collected and sequenced from patients from the Federation of Bosnia and Herzegovina, providing a comprehensive overview of the viral genetic diversity in this region. Two sequencing platforms, Ion Torrent and Illumina, were used, whereby 37 samples were sequenced on the Ion Torrent platform, while others were sequenced on the Illumina platform.ResultsThis study presents a genomic analysis of SARS-CoV-2 variants circulating in the Federation of Bosnia and Herzegovina over four distinct pandemic waves, spanning from March 2020 to April 2023. Examination of genomic variations across these waves revealed key mutations associated with transmission and potential virulence.ConclusionThese genomic insights into SARS-CoV-2 evolution in Federation of Bosnia and Herzegovina emphasizes the importance of continuous surveillance to understand viral evolution and strengthen public health responses to future pandemics.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"9287329251327020"},"PeriodicalIF":1.4,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144044012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Brain tumor detection using hybrid transfer learning and patch antenna-enhanced microwave imaging. 混合迁移学习和贴片天线增强微波成像的脑肿瘤检测。

IF 1.4 4区医学

Technology and Health Care Pub Date : 2025-04-10 DOI: 10.1177/09287329251325740

Deebu Usha Sudhakaran, Sreeja Thanka Swami Kanaka Bai

{"title":"Brain tumor detection using hybrid transfer learning and patch antenna-enhanced microwave imaging.","authors":"Deebu Usha Sudhakaran, Sreeja Thanka Swami Kanaka Bai","doi":"10.1177/09287329251325740","DOIUrl":"https://doi.org/10.1177/09287329251325740","url":null,"abstract":"BackgroundBrain tumors pose a significant healthcare challenge, necessitating early detection and precise monitoring to ensure effective treatment.ObjectivesThe study proposes an innovative technique with the integration of hybrid transfer learning with improved microwave imaging. The integration of special feature extraction abilities of pre-trained deep learning methods along with the high-resolution imaging capabilities of the patch antenna.MethodsIt was primarily composed of two phases. The initial stage involves the development of a patch antenna and head phantom model, which are then subjected to SAR analysis to extract pertinent features from transmitted signals. In the second stage, an AI-based detection model that utilizes MobileNet V2 is implemented. The images acquired by the patch antenna system are fed into MobileNet V2, which extracts high-level features by employing depth-wise separable convolutions and inverted residual blocks. The fully connected layer is used to classify brain tumors in an effective manner by passing these extracted features.ResultsThe results of the simulation indicate that the model performs exceptionally well, with an accuracy of 98.44%, precision of 98.03%, recall of 99.00%, F1-score of 98.52%, and specificity of 97.82%.ConclusionThis method offers a promising solution for the non-invasive and real-time detection of brain tumors, taking advantage of the electromagnetic properties of brain tissue and the capabilities of AI to address the limitations of current diagnostic methods, such as MRI and CT scans.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"9287329251325740"},"PeriodicalIF":1.4,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144046817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 1.4 4区医学

Technology and Health Care Pub Date : 2025-04-10 DOI: 10.1177/09287329251326022

Nancy M Ajwa

{"title":"Oral health-related quality of life of orthodontic clear aligner versus conventional fixed appliance during treatment: A prospective cohort study.","authors":"Nancy M Ajwa","doi":"10.1177/09287329251326022","DOIUrl":"https://doi.org/10.1177/09287329251326022","url":null,"abstract":"BackgroundOrthodontic clear aligners are a technologically advanced treatment modality that improves aesthetics and comfort while impacting patients' oral health-related quality of life (OHRQoL).ObjectiveThis study assessed and compared the OHRQoL of adult orthodontic patients receiving clear aligners and fixed appliances (metal and ceramic brackets) during orthodontic treatments.MethodologyOne hundred and five orthodontic patients were recruited and classified according to the treatment received. Group 1 clear aligners, group 2- fixed appliances/metal brackets, and Group 3-fixed appliances/ceramic brackets. The patients were surveyed using an Arabic version of the Oral Health Impact Profile 14 (OHIP- 14) questionnaire before (T0), 1-week (T1), and 3-months (T2) after the start of orthodontic treatment. Data was analysed using SPSS software at a significance level set at ≤0.05.ResultsThe mean OHIP scores showed no significant difference between the 3 groups at T0 (p = 0.09) and T2 (p = 0.41) time intervals. On the contrary, the mean OHIP scores at T1 significantly differed between 3 groups (p = 0.03). The mean OHIP scores within the groups at different time intervals was significantly different. Multiple comparison within the groups showed significant reduction in the mean OHIP scores from T0 to T1 and T2 period and further from T1 to T2 period, and the mean differences were statistically significant (p < 0.001).ConclusionAdult patients treated with clear aligners had significantly higher OHRQoL than those who underwent conventional fixed bracket-based treatment after 7 days of treatment but OHRQoL was similar after three months of treatment.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"9287329251326022"},"PeriodicalIF":1.4,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ultrasound guided stellate ganglion block for the treatment of tinnitus. 超声引导下的星状神经节阻滞治疗耳鸣。

IF 1.4 4区医学

Technology and Health Care Pub Date : 2025-03-28 DOI: 10.1177/09287329251324068

Xiaolan Qian, Liqing Zhao, Qiying Wang, Dingguo Liu, Gaigai Ma

{"title":"Ultrasound guided stellate ganglion block for the treatment of tinnitus.","authors":"Xiaolan Qian, Liqing Zhao, Qiying Wang, Dingguo Liu, Gaigai Ma","doi":"10.1177/09287329251324068","DOIUrl":"https://doi.org/10.1177/09287329251324068","url":null,"abstract":"BackgroundTinnitus, a common auditory disorder, significantly impacts patient quality of life and lacks universally effective treatments. The integration of advanced imaging technology like ultrasound in therapeutic interventions offers new possibilities in healthcare.ObjectiveThis study evaluated the efficacy of ultrasound-guided stellate ganglion block as an innovative approach to managing tinnitus.MethodsEighty patients with tinnitus were randomly assigned to either a control group receiving standard drug therapy or an observation group treated with ultrasound-guided stellate ganglion block in addition to standard therapy. Key metrics, including clinical effectiveness rates, anxiety scores, and tinnitus disability index scores, were assessed pre- and post-treatment.ResultsPost-treatment outcomes revealed that the observation group exhibited significantly improved anxiety scores (38.74 ± 4.05 vs. 50.45 ± 4.86; P < 0.05) and tinnitus disability index scores (37.8 ± 17.56 vs. 50.4 ± 21.26; P < 0.05) compared to the control group. Additionally, the observation group achieved a 100% clinical efficacy rate, outperforming the control group's 84% (P < 0.05).ConclusionUltrasound-guided stellate ganglion block demonstrates superior efficacy in managing tinnitus compared to conventional drug therapy. This study underscores the potential of integrating advanced ultrasound technology into healthcare to optimize treatment outcomes for auditory disorders.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"9287329251324068"},"PeriodicalIF":1.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143732709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Regulatory interplay between lncRNA-FGD5-AS1 and miR-17-5p in non-small cell lung cancer progression: Implications for novel therapeutic strategies. lncRNA-FGD5-AS1和miR-17-5p在非小细胞肺癌进展中的调控相互作用：对新治疗策略的影响

IF 1.4 4区医学

Technology and Health Care Pub Date : 2025-03-28 DOI: 10.1177/09287329251325336

Shufen Huo, Heng Zhang, Xiang Li, Xuan Li, Wenli Shang, Sen Sheng, Yingxuan Tian

{"title":"Regulatory interplay between lncRNA-FGD5-AS1 and miR-17-5p in non-small cell lung cancer progression: Implications for novel therapeutic strategies.","authors":"Shufen Huo, Heng Zhang, Xiang Li, Xuan Li, Wenli Shang, Sen Sheng, Yingxuan Tian","doi":"10.1177/09287329251325336","DOIUrl":"https://doi.org/10.1177/09287329251325336","url":null,"abstract":"BackgroundMicroRNA-17-5p (miR-17-5p) plays a pivotal role in the tumorigenesis and progression of non-small cell lung cancer (NSCLC) by regulating its target genes. Advances in molecular biology highlight the importance of long non-coding RNAs (lncRNAs) in cancer, yet the mechanistic interactions between miR-17-5p and lncRNAs in NSCLC remain underexplored.ObjectiveThis study investigated the regulatory interplay between miR-17-5p and lncRNA-FGD5-AS1 and evaluated their potential as targets for NSCLC therapy.MethodsA comprehensive set of technologies, including cell transfection, quantitative real-time PCR (qRT-PCR), bioinformatics analysis, and functional assays (proliferation, migration, apoptosis), was employed to examine the role of miR-17-5p and lncRNA-FGD5-AS1 in NSCLC.ResultsElevated lncRNA-FGD5-AS1 expression was observed in NSCLC cell lines A549 and H1299, correlating with poor patient prognosis. Functional assays revealed that miR-17-5p directly downregulates lncRNA-FGD5-AS1, thereby modulating key oncogenic processes. Overexpression of miR-17-5p reduced tumor cell proliferation and migration while inducing apoptosis. Conversely, miR-17-5p inhibition elevated lncRNA-FGD5-AS1 levels and reversed these effects.ConclusionThe findings identify the miR-17-5p/lncRNA-FGD5-AS1 regulatory axis as a novel therapeutic target for NSCLC. By integrating molecular and technological approaches, this study offers insights into precision oncology and highlights the potential for advanced RNA-based interventions.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"9287329251325336"},"PeriodicalIF":1.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143732708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FCM-NPOA: A hybrid Fuzzy C-means clustering with nomadic people optimizer for ovarian cancer detection. FCM-NPOA：一种混合模糊c均值聚类和游民优化器用于卵巢癌检测。

IF 1.4 4区医学

Technology and Health Care Pub Date : 2025-03-19 DOI: 10.1177/09287329241302736

S M Vijayarajan, V Purna Chandra Reddy, D Marlene Grace Verghese, Dattatray G Takale

{"title":"FCM-NPOA: A hybrid Fuzzy C-means clustering with nomadic people optimizer for ovarian cancer detection.","authors":"S M Vijayarajan, V Purna Chandra Reddy, D Marlene Grace Verghese, Dattatray G Takale","doi":"10.1177/09287329241302736","DOIUrl":"https://doi.org/10.1177/09287329241302736","url":null,"abstract":"Ovarian cancer is a highly prevalent cancer among women; However, it remains difficult to find effective pharmacological solutions to treat this deadly disease. However, early detection can significantly increase life expectancy. To address this issue, a predictive model for early diagnosis of ovarian cancer was developed by applying statistical techniques and machine learning models to clinical data from 349 patients. A hybrid evolutionary deep learning model was proposed by integrating genetic and histopathological imaging modalities within a multimodal fusion framework. Machine learning pipelines have been built using feature selection and dilution approaches to identify the most relevant genes for disease classification. A comparison was performed between the UNeT and transformer models for semantic segmentation, leading to the development of an optimized fuzzy C-means clustering algorithm (FCM-NPOA-PM-UI) for the classification of gynecological abdominopelvic tumors. Performing better than individual classifiers and other machine learning methods, the suggested ensemble model achieved an average accuracy of 98.96%, precision of 97.44%, and F1 score of 98.7%. With average Dice scores of 0.98 and 0.97 for positive tumors and 0.99 and 0.98 for malignant tumors, the Transformer model performed better in segmentation than the UNeT model. Additionally, we observed a 92.8% increase in accuracy when combining five machine learning models with biomarker data: random forest, logistic regression, SVM, decision tree, and CNN. These results demonstrate that the hybrid model significantly improves the accuracy and efficiency of ovarian cancer detection and classification, offering superior performance compared to traditional methods and individual classifiers.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"9287329241302736"},"PeriodicalIF":1.4,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Utilizing machine learning algorithms to identify biomarkers associated with Alzheimer's disease and ferroptosis-related genes. 利用机器学习算法确定与阿尔茨海默病和铁蛋白沉积相关基因有关的生物标记物。

IF 1.4 4区医学

Technology and Health Care Pub Date : 2025-03-03 DOI: 10.1177/09287329251322278

Di Wang, Chunsheng Lin, Gang Liu, Xin Wang, Shengwang Han, Zengxin Han

{"title":"Utilizing machine learning algorithms to identify biomarkers associated with Alzheimer's disease and ferroptosis-related genes.","authors":"Di Wang, Chunsheng Lin, Gang Liu, Xin Wang, Shengwang Han, Zengxin Han","doi":"10.1177/09287329251322278","DOIUrl":"https://doi.org/10.1177/09287329251322278","url":null,"abstract":"Background: Alzheimer's disease (AD) is a complex neurodegenerative disorder that complicates our understanding of its origins. Identifying AD-specific biomarkers can reveal its mechanisms and foster the development of innovative diagnostics and therapies, aiming to unlock new ways to combat this pervasive condition.Methods: We analyzed gene expression data using Weighted Gene Co-expression Network Analysis (WGCNA) and machine learning (random forest, lasso regression, and SVM-REF) to differentiate AD patients from controls and explore gene functions.Results: We identified 641 differentially expressed genes (DEGs) and 22 co-expressed genes, with functional enrichment analysis revealing their involvement in immune responses. Notably, EGR1 emerged as a potential diagnostic and therapeutic target.Conclusion: In our study, we applied WGCNA, DEGs and diverse machine learning approaches to uncover potential biomarkers linked to Alzheimer's Disease (AD) and ferroptosis. A particular hub gene emerged as a promising candidate for novel diagnostic and therapeutic markers specifically within the context of ferroptosis in AD. This discovery sheds new light on the pathogenesis of AD, potentially facilitating the development of groundbreaking diagnostic and therapeutic techniques.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"9287329251322278"},"PeriodicalIF":1.4,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143537974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0