Technology and Health Care最新文献_第9页

Research on lung cancer diagnosis based on machine learning. 基于机器学习的肺癌诊断研究。

IF 1.8 4区医学

Technology and Health Care Pub Date : 2026-03-01 Epub Date: 2025-07-17 DOI: 10.1177/09287329251358616

Haihui Huang, Aitong Zhong, Decheng Miao

{"title":"Research on lung cancer diagnosis based on machine learning.","authors":"Haihui Huang, Aitong Zhong, Decheng Miao","doi":"10.1177/09287329251358616","DOIUrl":"10.1177/09287329251358616","url":null,"abstract":"BackgroundIn clinical diagnosis, determining the level of malignancy in tumors and differentiating between benign and malignant tumors are common classification challenges. Accurate and early diagnosis is essential for targeted treatment, and machine learning methods can assist in making these judgments.MethodsThis paper focuses on the classification of the lung tissue as benign or malignant and assessing the degree of aggressiveness in lung cancer. The study employed artificial neural network (ANN), logistic regression, and ridge penalized logistic regression, which are methods without built-in feature selection. Additionally, lasso penalized logistic regression, elastic-net penalized logistic regression, and sparse logistic regression with the hybrid L1/2 + 2 regularization (HLR), which are methods with built-in feature selection, were also utilized.ResultsIn the study on classifying benign and malignant lung tissue, ANN demonstrated the best predictive performance among the methods without built-in feature selection, achieving an average test accuracy of 91.82%. Among the methods with built-in feature selection, HLR outperformed the others with an average test accuracy of 96.67%. When determining the level of malignancy in lung tumors, ANN surpassed other methods without built-in feature selection, attaining an average test accuracy of 84.74%. In comparison, HLR exceeded the performance of other methods with built-in feature selection, reaching an average test accuracy of 93.33%.ConclusionsThe experimental results indicated that HLR with built-in feature selection and ANN without built-in feature selection exhibited strong competitiveness among the methods investigated in both classifying benign and malignant lung tissue and assessing the degree of aggressiveness in lung cancer.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"40-50"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660866","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

Identification of cerebral infarction using bilateral photoplethysmography. 双侧光容积脉搏波识别脑梗死。

IF 1.8 4区医学

Technology and Health Care Pub Date : 2026-03-01 Epub Date: 2025-08-12 DOI: 10.1177/09287329251363294

Sang Yeon Kim, Hyun Goo Kang, YoungSuk Shin

{"title":"Identification of cerebral infarction using bilateral photoplethysmography.","authors":"Sang Yeon Kim, Hyun Goo Kang, YoungSuk Shin","doi":"10.1177/09287329251363294","DOIUrl":"10.1177/09287329251363294","url":null,"abstract":"BackgroundCerebral infarction is often associated with underlying cerebral vascular stenosis, such as carotid artery stenosis or cerebral artery stenosis due to arteriosclerosis. Existing imaging techniques, including carotid ultrasound, computed tomography angiography (CTA), and magnetic resonance angiography (MRA), are useful for diagnosis, but have limitations such as radiation exposure, contrast medium use side effects, and high cost. Therefore, the need for a simple, noninvasive, and cost-effective screening tool is emerging.ObjectiveIn this study, we propose a novel cerebral infarction screening technique using PPG signals measured from both index fingers for 120 s.MethodsPPG is a noninvasive optical technology that measures pulse waves that appear according to changes in blood volume. The collected waveforms were divided into windows and then normalized. Maximum Positive Amplitude (MPA) and Maximum Negative Amplitude (MNA) were extracted from each section, and the normal group and cerebral infarction patients were classified through linear discriminant analysis.ResultsAs a result of analyzing a total of 100 subjects (50 patients with cerebral infarction and 50 normal controls), the recognition rate based on MNA was 84%, MPA was 81%, and when the two indices were combined, it was 80%. Sensitivity was 80% for MNA and 72% for MPA, and specificity was 88% and 90%, respectively, suggesting that amplitude-based PPG indices can effectively reflect the presence or absence of cerebrovascular lesions.ConclusionThis study suggests the possibility of simply identifying patients with cerebral infarction by analyzing PPG signals of both fingers. The proposed technique can be used as a screening tool to complement existing imaging techniques, and is expected to contribute to reducing the burden of stroke through early diagnosis and preventive intervention in the future.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"187-196"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144823024","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

Research on arrhythmia recognition by using convolutional neural network in ECG images. 基于卷积神经网络的心电图像心律失常识别研究。

IF 1.3 4区医学

Technology and Health Care Pub Date : 2026-03-01 Epub Date: 2026-01-26 DOI: 10.1177/09287329251410734

Huan Zhang, Yu Zang, Liping Li, Chunhui Wang, Yanjun Li, Liang Jiang

{"title":"Research on arrhythmia recognition by using convolutional neural network in ECG images.","authors":"Huan Zhang, Yu Zang, Liping Li, Chunhui Wang, Yanjun Li, Liang Jiang","doi":"10.1177/09287329251410734","DOIUrl":"10.1177/09287329251410734","url":null,"abstract":"BackgroundDetermining the type of arrhythmia is crucial for prevention and early diagnosis of cardiovascular diseases.ObjectiveThis aims to address potential information loss caused by preprocessing, improve model performance, and accurately identify multiple types of arrhythmias.MethodsThis study proposes the use of wavelet transform denoising and convolutional neural network (CNN) model to classify and identify six types of arrhythmias. The original electrocardiosignal was transformed into a two-dimensional gray image by construction, and the data were amplified by fixed template clipping. Then, six arrhythmias were identified using an improved two-dimensional CNN model.ResultsThe classification accuracy, sensitivity, and specificity of the proposed method reached 90.50%, 81.70%, and 97.16%, respectively, and six types of arrhythmias were accurately identified.ConclusionsThe results showed that the wavelet transform as a preprocessing method can effectively improve the classification accuracy of the multiple types of arrhythmias. The method proposed in this study can provide a new reference for clinicians in diagnosing arrhythmia.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"111-123"},"PeriodicalIF":1.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146054751","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

Visual self-reporting for symptom communication in Parkinson's disease. 帕金森病症状交流的视觉自我报告。

IF 1.3 4区医学

Technology and Health Care Pub Date : 2026-03-01 Epub Date: 2026-02-05 DOI: 10.1177/09287329251414326

Wang-Jung Hur, Jeong-Woo Seo, Miso S Park, Ho-Ryong Yoo

{"title":"Visual self-reporting for symptom communication in Parkinson's disease.","authors":"Wang-Jung Hur, Jeong-Woo Seo, Miso S Park, Ho-Ryong Yoo","doi":"10.1177/09287329251414326","DOIUrl":"10.1177/09287329251414326","url":null,"abstract":"BackgroundThe Parkinson's Image Self (PIS) Report app was developed to complement standard clinician-rated assessments, such as the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS), by enabling patients to digitally self-report Parkinson's disease (PD) symptoms, including pain, tremor, rigidity, and emotional states.ObjectiveTo evaluate PIS Report validity and digital health utility by comparing patient-reported outcomes with clinician-rated MDS-UPDRS assessments.MethodsSeventy-eight PD participants completed baseline assessments; 70 provided week-8 follow-up data. PIS outcomes were compared with MDS-UPDRS items using ANOVA, correlation analysis, chi-square tests, and Cohen's kappa statistics.ResultsPIS-derived pain scores differed significantly across MDS-UPDRS pain strata (Item 1.9; F = 4.48, p < 0.01). Head/neck and upper limb pain correlated with perceived OFF periods (r = 0.46-0.48, p < 0.001), while head/neck and lower limb pain correlated negatively with happiness (r = -0.35 to -0.41, p < 0.001). Tremor reports showed fair agreement with clinician ratings (χ2 = 18.54, p < 0.001; κ = 0.36), whereas rigidity showed negligible agreement (χ2 = 0.00, p = 1.000; κ = 0.01).ConclusionThe PIS Report provides a structured digital tool enhancing patient-clinician communication and remote monitoring by capturing pain, OFF states, and emotional symptoms. Integration with wearables and telemedicine may advance patient-centered PD care.Trial RegistrationCRIS (KCT0006646); ClinicalTrials.gov (NCT05621772).","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"287-299"},"PeriodicalIF":1.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146127147","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

Bibliometric analysis of research on artificial İntelligence applications in breast cancer diagnosis. 人工İntelligence在乳腺癌诊断中的应用研究的文献计量学分析。

IF 1.8 4区医学

Technology and Health Care Pub Date : 2026-01-01 Epub Date: 2025-08-20 DOI: 10.1177/09287329251362602

Bengünur Ekinci, Hakan Tekedere

{"title":"Bibliometric analysis of research on artificial İntelligence applications in breast cancer diagnosis.","authors":"Bengünur Ekinci, Hakan Tekedere","doi":"10.1177/09287329251362602","DOIUrl":"10.1177/09287329251362602","url":null,"abstract":"ObjectiveThis analysis aims to examine studies on artificial intelligence (AI) applications in breast cancer diagnosis through bibliometric methods, focusing on temporal and geographical trends. It contributes to shaping the field's roadmap and helping researchers adapt to technological innovations.MethodA comprehensive search was conducted in the Web of Science (WOS) database. Bibliometric analyses of data from 2013-2024 were performed using VOSviewer and Bibliometrix R programs.ResultsThe analysis included 1537 articles. A significant rise in research activity was observed in 2019. The thematic analysis highlighted topics like histopathology, feature selection, deep learning, and machine learning. India was the most productive country with 405 studies. Keyword analysis showed increased usage of terms like transfer learning, CNN, and radiomics. U.S. was the most cited country with 7511 citations. Concept co-occurrence analysis revealed strong associations between terms such as feature selection, datasets, algorithm performance, and classification methods. Bejnordi's 2017 study was identified as the most influential, with 1909 citations.Discussion and ConclusionThis study identifies key authors, influential works, and trending topics, offering a broad understanding of the field's structure and evolution. It helps outline the advancements and emerging directions in AI applications for breast cancer diagnosis.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"3-15"},"PeriodicalIF":1.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12864533/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144884147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Retraction. 收缩。

IF 1.8 4区医学

Technology and Health Care Pub Date : 2026-01-01 Epub Date: 2025-11-11 DOI: 10.1177/09287329251390260

引用次数: 0

Instagram videos provide limited information on complications and return to social life regarding total knee arthroplasty: A multilingual analysis. Instagram视频提供了关于全膝关节置换术并发症和重返社会生活的有限信息：一项多语言分析。

IF 1.8 4区医学

Technology and Health Care Pub Date : 2026-01-01 Epub Date: 2025-09-18 DOI: 10.1177/09287329251367431

Yavuz Sahbat, Mustafa Fatih Dasci, Aziz Emre Nokay, Alicia Maria Ramos Tellez, Luigi Zanna, Abdulaziz Hariri, Serkan Surucu, Mustafa Citak

{"title":"Instagram videos provide limited information on complications and return to social life regarding total knee arthroplasty: A multilingual analysis.","authors":"Yavuz Sahbat, Mustafa Fatih Dasci, Aziz Emre Nokay, Alicia Maria Ramos Tellez, Luigi Zanna, Abdulaziz Hariri, Serkan Surucu, Mustafa Citak","doi":"10.1177/09287329251367431","DOIUrl":"10.1177/09287329251367431","url":null,"abstract":"IntroductionThe purpose of this study was to examine the content quality and potential shortcomings of arthroplasty training videos on Instagram.Materials and MethodsA search on Instagram was performed from November 1, 2023, to April 30, 2024. The hashtags Replacement, Total knee replacement and Knee arthroplasty were translated into 6 different languages and searched on Instagram by 6 observers who are native speakers of those languages. The videos were scored using the DISCERN score and Global Quality Score (GQS). The extent to which the videos addressed the processes about which patients need to be informed was also examined.ResultA total of 126 videos were analyzed in this study. The median DISCERN and GQS scores were 3.0 [1.0-5.0] and 3.0 [2.0-5.0], respectively. The most frequently mentioned subheading was arthroplasty procedure and prosthesis technology (74%), followed by treatment options (66%). The least mentioned subheading was complications (19%), followed by return to social life (44%).ConclusionsThe main finding of this study was that knee arthroplasty videos posted on Instagram were lacking in data. Video content largely describes surgical techniques but is insufficient to inform patients about postoperative processes. The video content quality was found to be moderately good according to both video quality scores, and these quality scores were moderately correlated with the mention of subheadings.","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"26-32"},"PeriodicalIF":1.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145087905","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

Expression of concern: "Digital virtual reduction combined with individualized guide plate of lateral tibial condyle osteotomy for the treatment of tibial plateau fracture". 关注表达：“数字虚拟复位联合个体化胫骨外侧髁截骨引导钢板治疗胫骨平台骨折”。

IF 1.8 4区医学

Technology and Health Care Pub Date : 2026-01-01 Epub Date: 2025-09-03 DOI: 10.1177/09287329251374381

引用次数: 0

Predicting hypertension using PPG sensor data and demographic factors: A machine learning approach. 利用PPG传感器数据和人口统计学因素预测高血压：一种机器学习方法。

IF 1.8 4区医学

Technology and Health Care Pub Date : 2026-01-01 Epub Date: 2025-09-17 DOI: 10.1177/09287329251375640

Feng-Qin Liu, Yingxia Mo

引用次数: 0

Retraction: Highly accurate brain tumor detection with high sensitivity using transform-based functions and machine learning algorithms. 缩回：使用基于变换的函数和机器学习算法进行高灵敏度的高精度脑肿瘤检测。

IF 1.8 4区医学