Health Informatics Journal最新文献_第5页

Cognitive behavioral intervention on digital addiction behavior among nursing students in Saudi Arabia. 认知行为干预对沙特护生数字成瘾行为的影响

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2026-04-01 Epub Date: 2026-04-24 DOI: 10.1177/14604582261444118

Vanitha Innocent Rani, Khalda Ahmed Mohammed Ahmed, Hanem Ahmed Abdelkhalek Ahmed, Shylaja Jeyapaul, Nawal Yahya H Asiri, Chithra Radhamany Arackal Thekkathil, Manal Abdu B Albishi, Hanan Awad Moawad Elmashad, Iman Awad Siddig Mohammed

{"title":"Cognitive behavioral intervention on digital addiction behavior among nursing students in Saudi Arabia.","authors":"Vanitha Innocent Rani, Khalda Ahmed Mohammed Ahmed, Hanem Ahmed Abdelkhalek Ahmed, Shylaja Jeyapaul, Nawal Yahya H Asiri, Chithra Radhamany Arackal Thekkathil, Manal Abdu B Albishi, Hanan Awad Moawad Elmashad, Iman Awad Siddig Mohammed","doi":"10.1177/14604582261444118","DOIUrl":"10.1177/14604582261444118","url":null,"abstract":"AimTo assess the effectiveness of a brief cognitive behavioral intervention (CBI) on digital dependence among nursing students in Saudi Arabia and to examine demographic and usage predictors of post-intervention outcomes.MethodsA pretest-posttest quasi-experimental study was conducted with 163 students (aged 18-23 years) at K' University. Participants completed the Digital Addiction Scale (DAS) before and after a three-session group CBI. Paired t-tests and correlations explored inter-domain relationships, and linear regressions examined predictors of post-intervention scores.ResultsMean DAS scores improved significantly for overuse (mean difference 0.40, p < .001), non-restraint (0.22, p = .010), and dependence (0.39, p < .001). Emotional state increased but not significantly (p = .135) and inhibiting the flow of life was unchanged (p = .742). Post-intervention overuse was predicted by daily hours of device use (β = 0.94 for 3-4 h; β = 1.04 for ≥7 h; all p < .05), while other demographic factors were non-significant.ConclusionA brief CBI improved behavioral aspects of digital dependence but had limited effect on emotional dimensions. Integrating culturally adapted CBIs and digital-wellness modules into nursing curricula could reduce digital distraction and enhance self-regulation. Further controlled studies are needed to validate and expand upon these results.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"32 2","pages":"14604582261444118"},"PeriodicalIF":2.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147789812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Interpretable heart disease risk prediction via FCA-constrained logistic regression. 基于fca约束的logistic回归的可解释心脏病风险预测。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2026-04-01 Epub Date: 2026-04-29 DOI: 10.1177/14604582261444612

Arman Salehi, Ashkan Heydarian, Hamid Reza Goudarzi, Zahra Farzin Rad

{"title":"Interpretable heart disease risk prediction via FCA-constrained logistic regression.","authors":"Arman Salehi, Ashkan Heydarian, Hamid Reza Goudarzi, Zahra Farzin Rad","doi":"10.1177/14604582261444612","DOIUrl":"10.1177/14604582261444612","url":null,"abstract":"ObjectiveTo develop an interpretable and clinically coherent heart disease risk prediction model by integrating Formal Concept Analysis (FCA) with a novel closure-constrained logistic regression that enforces coefficient coherence within FCA-derived concepts.MethodsWe used the Heart Disease Health Indicators dataset (BRFSS 2015; N≈380,000). Predictors were discretized into binary attributes, and closed itemsets were extracted via FCA. A closure penalty, which minimizes within-concept coefficient variance, was added to the logistic regression objective. Hyperparameters (closure strength λ, FCA minimum support) were selected using five-fold cross-validation on the training set. Baselines included L2-regularized logistic regression, Random Forest, and Gradient Boosting. Performance was evaluated on a held-out test set using AUC, accuracy, precision, recall, F1, PR-AUC, and Brier Score.ResultsOn the held-out test set, the FCA-constrained model achieved Accuracy = 0.906, AUC = 0.810, Precision = 0.709, Recall = 0.544, F1 = 0.556, PR-AUC = 0.265, and Brier Score = 0.078. Compared to baselines, the FCA model produced well-calibrated probabilities and the highest precision and F1-score, while providing concept-level explanations grounded in clinically coherent closed itemsets.ConclusionEmbedding FCA structure directly into model training yields an interpretable linear model with competitive discrimination and improved precision at clinically relevant thresholds.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"32 2","pages":"14604582261444612"},"PeriodicalIF":2.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147789865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Accessibility, acceptability and preferred modalities for a social media-based antenatal education program among pregnant women in Yaoundé, Cameroon. 喀麦隆雅温德省孕妇基于社交媒体的产前教育项目的可及性、可接受性和首选模式。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2026-04-01 Epub Date: 2026-05-21 DOI: 10.1177/14604582261455106

Fabrice Djouma Nembot, Claude Ngwayu Nkfusai, Collins Buh Nkum, Dora Ateudjieu, Deborah Kakapen, Zacheus Ebongo Nanje, Roger Ndzana, Francis Duhamel Nang Nang, Jerome Ateudjieu

{"title":"Accessibility, acceptability and preferred modalities for a social media-based antenatal education program among pregnant women in Yaoundé, Cameroon.","authors":"Fabrice Djouma Nembot, Claude Ngwayu Nkfusai, Collins Buh Nkum, Dora Ateudjieu, Deborah Kakapen, Zacheus Ebongo Nanje, Roger Ndzana, Francis Duhamel Nang Nang, Jerome Ateudjieu","doi":"10.1177/14604582261455106","DOIUrl":"10.1177/14604582261455106","url":null,"abstract":"BackgroundSocial media platforms are increasingly considered cost-effective channels for delivering antenatal health education in settings where maternal and neonatal mortality remain high. This study assessed accessibility, acceptability, and preferred modalities of a social media-based antenatal care (ANC) program among pregnant women.MethodsWe conducted a cross-sectional survey among pregnant women attending their first ANC visit at a major urban facility in Yaoundé. Data were collected using semi-structured questionnaires and analyzed using descriptive statistics and multivariate logistic regression.ResultsAmong 411 participants (mean age 27.5 ± 6.5 years), 89.1% owned a smartphone. WhatsApp was universally used among smartphone owners, followed by Facebook (84.7%) and TikTok (53.6%). Overall, 83.5% expressed willingness to participate in the proposed program. Videos (60.9%), text messages (51.0%), and images (44.6%) were the most preferred formats, with 56.9% favoring daily delivery. Independent predictors of acceptance included age ≥25 years (aOR 4.23, 95%CI:1.86-9.61), secondary education (aOR 2.97, 95%CI:1.06-8.34), and daily WhatsApp use (aOR 2.85, 95%CI:1.45-5.58), while intimate partner violence history was negatively associated (aOR 0.37, 95%CI:0.15-0.95).ConclusionA WhatsApp-based ANC education program is highly acceptable in this urban setting. Sociodemographic, digital engagement, and psychosocial factors should inform tailored, privacy-sensitive implementation within routine ANC services.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"32 2","pages":"14604582261455106"},"PeriodicalIF":2.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147984453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Optimizing nursing clinical decision support systems: Insights from nurses' experiences. 优化护理临床决策支持系统：来自护士经验的见解。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2026-04-01 Epub Date: 2026-05-27 DOI: 10.1177/14604582261455122

Qi Zhang, Aliaya Adili, Zhenghong Yu, Wei Qin, Zheng Zhu, Yuxia Zhang

{"title":"Optimizing nursing clinical decision support systems: Insights from nurses' experiences.","authors":"Qi Zhang, Aliaya Adili, Zhenghong Yu, Wei Qin, Zheng Zhu, Yuxia Zhang","doi":"10.1177/14604582261455122","DOIUrl":"10.1177/14604582261455122","url":null,"abstract":"PurposeThis study explores nurses' experiences with a Nursing Clinical Decision Support System (Nu-CDSS) two years post-implementation and identifies user-centered areas for system optimization.MethodsA descriptive qualitative study was conducted in a tertiary acute care hospital in Shanghai. A select, stratified group of 15 Chinese-speaking clinical nurses and nurse managers across five wards participated in in-depth semi-structured interviews. Data were transcribed verbatim and analyzed thematically with findings organized using the 5R framework.ResultsSeven themes and 14 subthemes were identified. Optimization requirements encompassed: 1) Right Information: enhancing clinical relevance and patient-specific adaptability of diagnoses and interventions; 2) Right People: optimizing role-based usability; 3) Right Formats: integrating clinical records and embedding notifications directly into primary workflows; 4) Right Channels: improving platform interoperability and seamless mobile-desktop data synchronization; 5) Right Time: minimizing system latency and optimizing reminder timing and lifecycles. Furthermore, participants emphasized the need for 6) robust technical and network support, including adaptive inference engines, and 7) standardized nursing protocols.ConclusionOptimizing Nu-CDSS in acute care requires improvements in the knowledge base, interface integration, platform synchronization, reminder timing, and technical support. Future iterations should incorporate AI-enhanced, context-sensitive decision support while preserving nurses' clinical judgment.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"32 2","pages":"14604582261455122"},"PeriodicalIF":2.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148037699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Integrating platform usage into the comprehensive model of information seeking: Health information seeking on WeChat among Chinese young adults. 将平台使用融入信息搜索综合模型：中国年轻人在微信上的健康信息搜索。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2026-04-01 Epub Date: 2026-06-25 DOI: 10.1177/14604582261463699

QianYing Ma, Jen-Sern Tham

{"title":"Integrating platform usage into the comprehensive model of information seeking: Health information seeking on WeChat among Chinese young adults.","authors":"QianYing Ma, Jen-Sern Tham","doi":"10.1177/14604582261463699","DOIUrl":"10.1177/14604582261463699","url":null,"abstract":"BackgroundWeChat has become a central platform for health information seeking in China, particularly among young adults. Understanding the mechanisms underlying this behavior is crucial for improving digital health literacy and designing effective interventions.ObjectiveThis study applies the Comprehensive Model of Information Seeking (CMIS) to examine how WeChat use shapes users' perceptions of health information characteristics and utility, influencing health information-seeking behaviors among Chinese young adults.MethodsData were obtained from a cross-sectional online survey of 890 WeChat users aged 18-35 conducted in May 2024. Structural equation modeling (SEM) and the PROCESS macro were applied to test the hypothesized associations and mediating mechanisms involving perceived characteristics and utility.ResultsWeChat use, salience, and beliefs predicted perceived utility. Perceived characteristics and utility were positively associated with health information-seeking behaviors and mediated the relationship with WeChat use both in parallel and sequentially.ConclusionIntegrating platform-specific use into CMIS can promote health information seeking and inform digital health communication.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"32 2","pages":"14604582261463699"},"PeriodicalIF":2.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148320741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Determining the essential data elements of a comprehensive registry system for patients with leishmaniasis. 确定利什曼病患者综合登记系统的基本数据要素。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2026-04-01 Epub Date: 2026-06-22 DOI: 10.1177/14604582261463681

Ahmadreza Shamsabadi, Aliasghar Neshat, Fateme Molaalinejad, Esmaeil Mehraeen

{"title":"Determining the essential data elements of a comprehensive registry system for patients with leishmaniasis.","authors":"Ahmadreza Shamsabadi, Aliasghar Neshat, Fateme Molaalinejad, Esmaeil Mehraeen","doi":"10.1177/14604582261463681","DOIUrl":"10.1177/14604582261463681","url":null,"abstract":"IntroductionStandardizing patient data collection and analysis facilitates accurate reporting and enhances communication among healthcare teams. Given the high prevalence of leishmaniasis in specific geographic regions of Iran and the critical role of registry systems, this study aimed to identify the essential data elements required for developing a comprehensive registry system for patients with leishmaniasis.MethodsThis descriptive-applied study was conducted in 2024 in two phases: a literature review (2011-2024) to identify data elements for leishmaniasis, followed by expert consultation to prepare an initial draft of the minimum data set.ResultsA total of 60 data elements with a content validity ratio (CVR) ≥ 0.75 were confirmed and organized into 10 subgroups for the comprehensive leishmaniasis registry. The subgroups comprised: geographic location of registration; identity and demographic information; travel and changes of residence; characteristics of the patient's dwelling; medical history and current medications; prior history of leishmaniasis; disease-specific information; laboratory data; therapeutic interventions; and follow-up of treatment discontinuation.ConclusionConsidering the pivotal role of registry systems in disease management, prevention, treatment, and resource allocation, designing a comprehensive registry-particularly for endemic and region-specific diseases such as leishmaniasis is essential.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"32 2","pages":"14604582261463681"},"PeriodicalIF":2.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148304023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Triple-stack geostatistical modeling for urban injury: Integrating grids, built environment, and Poisson kriging for pedestrian fatalities in Cali, Colombia. 城市伤害的三叠地统计模型：整合网格、建筑环境和泊松克里格对哥伦比亚卡利行人死亡的研究。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2026-04-01 Epub Date: 2026-05-31 DOI: 10.1177/14604582261456889

Lani Fox, Marc Serre, Daniel A Rodríguez, Shrikant I Bangdiwala, Andrés Villaveces

{"title":"Triple-stack geostatistical modeling for urban injury: Integrating grids, built environment, and Poisson kriging for pedestrian fatalities in Cali, Colombia.","authors":"Lani Fox, Marc Serre, Daniel A Rodríguez, Shrikant I Bangdiwala, Andrés Villaveces","doi":"10.1177/14604582261456889","DOIUrl":"10.1177/14604582261456889","url":null,"abstract":"We introduce a novel geostatistical framework to map and predict pedestrian fatalities in Cali, Colombia (2008-2010), addressing critical gaps in research on built environment risk factors particularly in low- and middle-income countries. We triple stack: (1) a grid-based global moving window reducing the modifiable areal unit problem, redistributing events and population; (2) a Poisson-based land use regression incorporating built environment data; and (3) Poisson kriging addressing small number issues. Nine built environment variables were significant predictors of pedestrian fatalities. Health centers had the highest risk increase (54%), while parks and population density were protective. The triple-stack model markedly improved risk prediction, sharpening hotspot delineation and reducing background noise; at high population densities, predictive errors were as low as 0.26 deaths. The framework is a transferable tool for other urban contexts; thus, we provide method decision-making support helping users select between a simplified, codeless, GUI based platform or an advanced, custom-coded approach. Our results demonstrate gains in model predictive accuracy may be primarily attributable to the first two layers, the grid and LUR. Although, Poisson kriging is traditionally used to address the \"small number problem,\" the first two layers may substantially stabilize rates, resulting in more realistic, interpretable risk maps.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"32 2","pages":"14604582261456889"},"PeriodicalIF":2.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148102419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Nurses' adaptation to digital transformation in healthcare: A grounded theory of progressive digital adaptation. 护士对医疗数字化转型的适应：渐进式数字化适应的基础理论。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2026-04-01 Epub Date: 2026-04-02 DOI: 10.1177/14604582261440411

Ebtsam Aly Abou Hashish, Noura Mohamed Abdel Razek

{"title":"Nurses' adaptation to digital transformation in healthcare: A grounded theory of progressive digital adaptation.","authors":"Ebtsam Aly Abou Hashish, Noura Mohamed Abdel Razek","doi":"10.1177/14604582261440411","DOIUrl":"10.1177/14604582261440411","url":null,"abstract":"BackgroundDigital transformation in healthcare requires nurses to use new technologies while maintaining care quality. Adaptation becomes challenging in resource-limited settings where training, support, and infrastructure vary and where nurses often face competing demands.ObjectiveThis study aimed to develop a grounded theory explaining how nurses progressively adapt to digital transformation, the conditions that facilitate or hinder their movement, and the strategies they use to manage challenges.MethodsA grounded theory design guided the study. Thirty nurses in an Egyptian private hospital participated in in-depth semi-structured interviews conducted over four months. Data collection and analysis followed constant comparison and continued until theoretical saturation.ResultsThe study produced the Progressive Digital Adaptation theory. Two trajectories were identified. The sustaining trajectory showed confident and continuous integration, while the struggling trajectory reflected resistance or stalled movement. Five themes shaped adaptation. These were recurring resistance to technology, iterative learning and skill acquisition, integration into clinical routines, contextual factors influencing progression, and mechanisms supporting sustained transformation.ConclusionsEffective digital adaptation depends on consistent organizational commitment. The theory clarifies how nurses progress or regress between stages and identifies practical targets for interventions that strengthen digital transformation in varied healthcare settings.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"32 2","pages":"14604582261440411"},"PeriodicalIF":2.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147596360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Predicting mortality risk of COVID-19 among chronic kidney disease patients using machine learning algorithms. 利用机器学习算法预测慢性肾病患者COVID-19的死亡风险。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2026-04-01 Epub Date: 2026-04-03 DOI: 10.1177/14604582261425071

Raoof Nopour

{"title":"Predicting mortality risk of COVID-19 among chronic kidney disease patients using machine learning algorithms.","authors":"Raoof Nopour","doi":"10.1177/14604582261425071","DOIUrl":"10.1177/14604582261425071","url":null,"abstract":"Objective: COVID-19 disease has a high prevalence and mortality rate among chronic kidney disease patients. Previous studies have shown that ML-based prediction models are effective for developing preventive strategies. Despite several efforts to establish prediction models for COVID-19 mortality risk among different populations, few studies have focused on COVID-19 mortality among patients with chronic kidney disease. The current study aimed to develop an effective, efficient preventive strategy to improve prognosis and survival among these patients by constructing a machine-learning-based prediction model. Methods: The current retrospective study used single-center data from 556 hospitalized patients with CKD. All patients in the cohort had respiratory failure following COVID-19. We leveraged ensemble and non-ensemble algorithms to construct a prediction model and scored the chosen features for better interpretability. Results: The empirical results of this study showed that XG-Boost achieved an AU-ROC of 0.921 with a 95% CI of [0.906-0.941] and an AU-ROC of 0.851 with a 95% CI of [0.835-0.877] in training and validation modes, respectively, yielding more favourable predictive performance than the models. Conclusion: XG-Boost demonstrated predictive merit that can be leveraged as an auxiliary tool to aid clinicians in making more informed decisions in clinical settings.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"32 2","pages":"14604582261425071"},"PeriodicalIF":2.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147610703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Editorial: AI and robotics for the smart hospitals of the future. 社论：未来智能医院的人工智能和机器人技术。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2026-04-01 Epub Date: 2026-06-23 DOI: 10.1177/14604582261462839

Antonios Billis, Emmanouil Rigas, Izidor Mlakar, Patrick Weber, Lacramioara Stoicu-Tivadar

引用次数: 0