Health Informatics Journal最新文献

Presentation suitability and readability of ChatGPT's medical responses to patient questions about on knee osteoarthritis. ChatGPT对患者膝关节骨关节炎问题的医学回应的呈现、适用性和可读性

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2025-01-01 DOI: 10.1177/14604582251315587

Myungeun Yoo, Chan Woong Jang

{"title":"Presentation suitability and readability of ChatGPT's medical responses to patient questions about on knee osteoarthritis.","authors":"Myungeun Yoo, Chan Woong Jang","doi":"10.1177/14604582251315587","DOIUrl":"https://doi.org/10.1177/14604582251315587","url":null,"abstract":"Objective: This study aimed to evaluate the presentation suitability and readability of ChatGPT's responses to common patient questions, as well as its potential to enhance readability. Methods: We initially analyzed 30 ChatGPT responses related to knee osteoarthritis (OA) on March 20, 2023, using readability and presentation suitability metrics. Subsequently, we assessed the impact of detailed and simplified instructions provided to ChatGPT for same responses, focusing on readability improvement. Results: The readability scores for responses related to knee OA significantly exceeded the recommended sixth-grade reading level (p < .001). While the presentation of information was rated as \"adequate,\" the content lacked high-quality, reliable details. After the intervention, readability improved slightly for responses related to knee OA; however, there was no significant difference in readability between the groups receiving detailed versus simplified instructions. Conclusions: Although ChatGPT provides informative responses, they are often difficult to read and lack sufficient quality. Current capabilities do not effectively simplify medical information for the general public. Technological advancements are needed to improve user-friendliness and practical utility.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"31 1","pages":"14604582251315587"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016851","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

Advancing African American and hispanic health literacy with a bilingual, personalized, prevention smartphone application. 通过双语、个性化、预防智能手机应用程序推进非裔美国人和西班牙裔美国人的健康素养。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2025-01-01 DOI: 10.1177/14604582251315604

Neil Jay Sehgal, Devlon Nicole Jackson, Christine Herlihy, John Dickerson, Cynthia Baur

{"title":"Advancing African American and hispanic health literacy with a bilingual, personalized, prevention smartphone application.","authors":"Neil Jay Sehgal, Devlon Nicole Jackson, Christine Herlihy, John Dickerson, Cynthia Baur","doi":"10.1177/14604582251315604","DOIUrl":"https://doi.org/10.1177/14604582251315604","url":null,"abstract":"Many online health information sources are generic and difficult to understand, but consumers want information to be personalized and understandable. Smartphone health applications (apps) offer personalized information to support health goals and reduce preventable chronic conditions. This study aimed to determine how the HealthyMe/MiSalud personalized app (1) engaged English-speaking African American and Spanish-speaking Hispanic adults, and (2) motivated them to set goals and follow preventive recommendations. Our study adds to the literature on digital health, health information seeking, and prevention. We used a multi-method approach, including community and participatory design principles, to learn about potential African American and Hispanic adult health app users and evaluate the app in two usability tests and a 12-month field test. Ninety-six African American and Hispanic adults downloaded the HealthyMe/MiSalud app and used it for a minimum of 36 weeks. We found they wanted personalized information on core prevention topics, and their health histories and goals affected how they rated topic relevance. African American females ages 18-34 were more likely to save an article aligned with family health history, and African American females aged 35-49, males age 50-64, and African American males overall were more likely to save an article aligned with their health goals. Our study revealed that a prevention app with personalized recommendations can support health information seeking and health literacy. These findings can help app developers, public health practitioners, and researchers when designing apps for groups of varying identities.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"31 1","pages":"14604582251315604"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016828","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

Pathways to usage intention of mobile health apps among hypertensive patients: A fuzzy-set qualitative comparative analysis. 高血压患者移动健康app使用意向的路径：模糊集定性比较分析

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2025-01-01 DOI: 10.1177/14604582251315600

Ting Sun, Zenghui Ding, Hui Xie, Xiaoning Chen, Yumeng Wang, Yibin Li, Guoli Zhang, Xuejie Xu, Yuxin Xia, Zuchang Ma

{"title":"Pathways to usage intention of mobile health apps among hypertensive patients: A fuzzy-set qualitative comparative analysis.","authors":"Ting Sun, Zenghui Ding, Hui Xie, Xiaoning Chen, Yumeng Wang, Yibin Li, Guoli Zhang, Xuejie Xu, Yuxin Xia, Zuchang Ma","doi":"10.1177/14604582251315600","DOIUrl":"https://doi.org/10.1177/14604582251315600","url":null,"abstract":"Background: The efficacy of mHealth apps in managing hypertension has been proven; however, low usage intention remains a significant challenge, warranting an in-depth exploration of the influencing factors. Objectives: This study aimed to examine the factors influencing hypertensive new users' intention to use mobile health applications through a cross-sectional survey. Methods: Fuzzy-set qualitative comparative analysis (fsQCA) was employed to investigate the combinations of various determinants, including technology acceptance, adoption factors, compliance behavior initiation factors, and time motivation factors for decision making. Results: A total of 100 middle-aged and elderly hypertensive individuals participated in the survey, with 98 responses included in the final statistical analysis. The analysis identified four distinct configurations that contribute to high usage intentions, with solution consistency and coverage values of 0.93 and 0.36, respectively. Conclusion: The findings suggest that intervention strategies should account for the various pathways leading to usage intentions.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"31 1","pages":"14604582251315600"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016847","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

Evaluating the quality of Spanish-language information for patients with type 2 diabetes on YouTube and Facebook. 评估YouTube和Facebook上针对2型糖尿病患者的西班牙语信息的质量。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2025-01-01 DOI: 10.1177/14604582251315592

María Juliana Soto-Chávez, Candida Díaz-Brochero, Ana María Gómez-Medina, Diana Cristina Henao, Oscar Mauricio Muñoz

{"title":"Evaluating the quality of Spanish-language information for patients with type 2 diabetes on YouTube and Facebook.","authors":"María Juliana Soto-Chávez, Candida Díaz-Brochero, Ana María Gómez-Medina, Diana Cristina Henao, Oscar Mauricio Muñoz","doi":"10.1177/14604582251315592","DOIUrl":"https://doi.org/10.1177/14604582251315592","url":null,"abstract":"Introduction: Spanish speakers rely on social media for health information, with varying quality of its content. This study evaluates the reliability, completeness, and quality of type 2 diabetes (T2D) information available in Spanish-language videos on YouTube and Facebook. Methods: Analytical observational study that included Spanish-language videos on TD2 available on Facebook and YouTube. General characteristics, interaction and generating sources are described. Standardized tools were used to assess reliability, completeness and overall quality. Results: We included 172 videos, 90 from Youtube® and 82 from Facebook®. The median number of views was 1725 (IQR 213-10,000), with an average duration of 5.93 minutes (IQR 3.2-16.8) and an internet time of 834 days (IQR 407-1477). Most videos were uploaded by independent users (58.72%). Reliability (evaluated with DISCERN tool) had a median of 3 (IQR 2-3), completeness (content score) had a median of 2 (IQR 1-3), and overall quality, evaluated with the Global Quality Score (GQS) tool had a median of 3 (IQR 3-4). Using a global classification of \"subjective reliability\" 92.4% of the videos were considered reliable. Better completeness was observed in Facebook videos (p < .001). Reliability was better for videos from government or news organizations. Conclusion: Our results suggest that videos about T2D in Spanish on social media such as YouTube and Facebook have good reliability and quality, with greater exhaustiveness in content in Facebook videos and greater reliability for videos from government or news organizations.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"31 1","pages":"14604582251315592"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016841","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 metabolic syndrome: Machine learning techniques for improved preventive medicine. 预测代谢综合征：改进预防医学的机器学习技术。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2025-01-01 DOI: 10.1177/14604582251315602

Orit Goldman, Ofir Ben-Assuli, Shimon Ababa, Ori Rogowski, Shlomo Berliner

{"title":"Predicting metabolic syndrome: Machine learning techniques for improved preventive medicine.","authors":"Orit Goldman, Ofir Ben-Assuli, Shimon Ababa, Ori Rogowski, Shlomo Berliner","doi":"10.1177/14604582251315602","DOIUrl":"https://doi.org/10.1177/14604582251315602","url":null,"abstract":"Objectives: Metabolic syndrome (MetS) has a significant impact on health. MetS is the umbrella term for a group of interdependent metabolic threats that contribute to the emergence of diseases that can lead to death. This study was designed to better predict the risks associated with MetS to enable medical personnel to make more optimal preventive medical decisions. Study design: Data from a large hospital survey database was used to train data mining classification techniques to predict patient-level risk subsequent to extensive data engineering that included aggregating predictors from multiple visits. Methods: A prospective group of seemingly healthy volunteers from the database was studied based on data obtained during their regular annual health checkups. Results: After aggregating the variables over time, the findings indicated that the predictive power of our model outperformed methods presented in other studies (AUC = 0.947). Specific lifestyle factors were identified as contributing to MetS. Conclusion: Involvement to avoid recurring diseases can significantly decrease medical problems and treatment expenses. The findings emphasize the importance of using predictive tools in healthcare and preventive medicine. The results can be used for future prevention strategies that encourage lifestyle changes and implement directed medical treatment protocols to decrease the burden of illness.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"31 1","pages":"14604582251315602"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016849","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

A blueprint for large language model-augmented telehealth for HIV mitigation in Indonesia: A scoping review of a novel therapeutic modality. 印度尼西亚用于减轻艾滋病毒的大型语言模型增强远程保健蓝图：对一种新型治疗方式的范围审查。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2025-01-01 DOI: 10.1177/14604582251315595

Daniel Busch, Choiru Za'in, Hei Man Chan, Agnes Haryanto, Wahyudi Agustiono, Kan Yu, Kyra Hamilton, Jeroen Kroon, Wei Xiang

{"title":"A blueprint for large language model-augmented telehealth for HIV mitigation in Indonesia: A scoping review of a novel therapeutic modality.","authors":"Daniel Busch, Choiru Za'in, Hei Man Chan, Agnes Haryanto, Wahyudi Agustiono, Kan Yu, Kyra Hamilton, Jeroen Kroon, Wei Xiang","doi":"10.1177/14604582251315595","DOIUrl":"https://doi.org/10.1177/14604582251315595","url":null,"abstract":"Background: The HIV epidemic in Indonesia is one of the fastest growing in Southeast Asia and is characterised by a number of geographic and sociocultural challenges. Can large language models (LLMs) be integrated with telehealth (TH) to address cost and quality of care? Methods: A literature review was performed using the PRISMA-ScR (2018) guidelines between Jan 2017 and June 2024 using the PubMed, ArXiv and semantic scholar databases. Results: Of the 694 records identified, 12 studies met the inclusion criteria. Although the role of eHealth interventions as well as telehealth in HIV management appears well established, there is a significant literature gap on the integration of telehealth and LLM technology. To address this, we provide a blueprint for the safe and ethical integration of LLM-TH into triage, history taking, patient education highlighting opportunities for reduced consultation time and improved quality of care. Conclusions: Variable access to mobile technology and the need for empirical validation stand out as limitations for LLM-TH. However, we argue that the current evidence base suggests the benefits far outweigh the challenges in applying LLM-TH for HIV care in Indonesia. We also argue this novel therapeutic modality is broadly applicable to the subacute general practice setting.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"31 1","pages":"14604582251315595"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016825","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

Researching public health datasets in the era of deep learning: a systematic literature review.

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2025-01-01 DOI: 10.1177/14604582241307839

Rand Obeidat, Izzat Alsmadi, Qanita Bani Baker, Aseel Al-Njadat, Sriram Srinivasan

{"title":"Researching public health datasets in the era of deep learning: a systematic literature review.","authors":"Rand Obeidat, Izzat Alsmadi, Qanita Bani Baker, Aseel Al-Njadat, Sriram Srinivasan","doi":"10.1177/14604582241307839","DOIUrl":"https://doi.org/10.1177/14604582241307839","url":null,"abstract":"Objective: Explore deep learning applications in predictive analytics for public health data, identify challenges and trends, and then understand the current landscape. Materials and Methods: A systematic literature review was conducted in June 2023 to search articles on public health data in the context of deep learning, published from the inception of medical and computer science databases through June 2023. The review focused on diverse datasets, abstracting applications, challenges, and advancements in deep learning. Results: 2004 articles were reviewed, identifying 14 disease categories. Observed trends include explainable-AI, patient embedding learning, and integrating different data sources and employing deep learning models in health informatics. Noted challenges were technical reproducibility and handling sensitive data. Discussion: There has been a notable surge in deep learning applications on public health data publications since 2015. Consistent deep learning applications and models continue to be applied across public health data. Despite the wide applications, a standard approach still does not exist for addressing the outstanding challenges and issues in this field. Conclusion: Guidelines are needed for applying deep learning and models in public health data to improve FAIRness, efficiency, transparency, comparability, and interoperability of research. Interdisciplinary collaboration among data scientists, public health experts, and policymakers is needed to harness the full potential of deep learning.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"31 1","pages":"14604582241307839"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142967370","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

HealthCheck: A method for evaluating persuasive mobile health applications. HealthCheck：评估有说服力的移动健康应用的方法。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2024-10-01 DOI: 10.1177/14604582241290969

Shweta Premanandan, Awais Ahmad, Åsa Cajander, Sami Pohjolainen, Pär Ågerfalk, Mikko Rajanen, Lisette van Gemert-Pijnen

{"title":"HealthCheck: A method for evaluating persuasive mobile health applications.","authors":"Shweta Premanandan, Awais Ahmad, Åsa Cajander, Sami Pohjolainen, Pär Ågerfalk, Mikko Rajanen, Lisette van Gemert-Pijnen","doi":"10.1177/14604582241290969","DOIUrl":"https://doi.org/10.1177/14604582241290969","url":null,"abstract":"Objectives: This paper introduces HealthCheck, a novel evaluation method for persuasive mobile health applications, aiming to fill the critical gap in quick and effective evaluation tools for this domain. Methods: Following Design Science Research, HealthCheck was developed through problem identification, solution design, implementation, evaluation, and iterative refinement. The implementation involved testing with seven experts to assess its applicability and effectiveness. Results: Feedback from the evaluators indicated that while a few heuristics in HealthCheck were considered irrelevant by some, the majority found the heuristics to be both pertinent and beneficial, especially within the caregiving context. This feedback highlights the practical value of HealthCheck and its potential to offer meaningful insights into improving the usability of persuasive eHealth applications. Conclusion: The study shows HealthCheck effectively evaluates persuasive mobile health applications, offering actionable insights to enhance usability. This validates the relevance and robustness of HealthCheck's heuristics, advancing information systems and human-computer interaction research.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"30 4","pages":"14604582241290969"},"PeriodicalIF":2.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142395433","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

Perceived benefits and challenges of using an electronic cancer prediction system for safety netting in primary care: An exploratory study of C the signs. 使用电子癌症预测系统为初级保健提供安全网的好处和挑战：对 C the signs 的探索性研究。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2024-10-01 DOI: 10.1177/14604582241279742

Sara Spear, Pamela Knight-Davidson

{"title":"Perceived benefits and challenges of using an electronic cancer prediction system for safety netting in primary care: An exploratory study of C the signs.","authors":"Sara Spear, Pamela Knight-Davidson","doi":"10.1177/14604582241279742","DOIUrl":"https://doi.org/10.1177/14604582241279742","url":null,"abstract":"Objectives: This paper reports on an exploratory study into the perceived benefits and challenges of using an electronic cancer prediction system, C the Signs, for safety netting within a Primary Care Network (PCN) in the East of England.Methods: The study involved semi-structured interviews and a qualitative questionnaire with a sample of 15 clinicians and practice administrators within four GP practices in the PCN.Results: Participants generally perceived benefits of C the Signs for managing and monitoring referrals as part of post-consultation safety netting. Clinicians made little use of the decision support function though, as part of safety netting during the consultation, and referrals were still sent by administrators, rather than directly by clinicians through C the Signs.Conclusion: Emphasising the benefits of C the Signs for post-consultation safety netting is most likely to gain buy-in to the system from clinicians, and can also be used by administrators for shared visibility of referrals. More evidence is needed on the value of C the Signs for safety netting during the consultation, through better diagnosis of cancer, before this is seen as a valued benefit by clinicians and provides motivation to use the system.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"30 4","pages":"14604582241279742"},"PeriodicalIF":2.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142407223","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 subgroup learning-based modeling framework: Study of diabetic kidney disease prediction. 基于子群学习的可解释建模框架：糖尿病肾病预测研究。

IF 2.2 3区医学

Health Informatics Journal Pub Date : 2024-10-01 DOI: 10.1177/14604582241291379

Bo Liu, Xiangzhou Zhang, Kang Liu, Xinhou Hu, Eric W T Ngai, Weiqi Chen, Ho Yin Chan, Yong Hu, Mei Liu

{"title":"Interpretable subgroup learning-based modeling framework: Study of diabetic kidney disease prediction.","authors":"Bo Liu, Xiangzhou Zhang, Kang Liu, Xinhou Hu, Eric W T Ngai, Weiqi Chen, Ho Yin Chan, Yong Hu, Mei Liu","doi":"10.1177/14604582241291379","DOIUrl":"https://doi.org/10.1177/14604582241291379","url":null,"abstract":"Objectives: Complex diseases, like diabetic kidney disease (DKD), often exhibit heterogeneity, challenging accurate risk prediction with machine learning. Traditional global models ignore patient differences, and subgroup learning lacks interpretability and predictive efficiency. This study introduces the Interpretable Subgroup Learning-based Modeling (iSLIM) framework to address these issues.Methods: iSLIM integrates expert knowledge with a tree-based recursive partitioning approach to identify DKD subgroups within an EHR dataset of 11,559 patients. It then constructs separate models for each subgroup, enhancing predictive accuracy while preserving interpretability.Results: Five clinically relevant subgroups are identified, achieving an average sensitivity of 0.8074, outperforming a single global model by 0.1104. Post hoc analyses provide pathological and biological evidence supporting subgroup validity and potential DKD risk factors.Conclusion: The iSLIM surpasses traditional global model in predictive performance and subgroup-specific risk factor interpretation, enhancing the understanding of DKD's heterogeneous mechanisms and potentially increasing the adoption of machine learning models in clinical decision-making.","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"30 4","pages":"14604582241291379"},"PeriodicalIF":2.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481346","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