The COVID-19 pandemic has been a watershed moment in public health surveillance, highlighting the crucial role of data-driven insights in informing health actions and policies. Revisiting key concepts— public health, epidemiology in public health practice, public health surveillance, and public health informatics—lays the foundation for understanding how these elements converge to create a robust public health surveillance system framework. Especially during the COVID-19 pandemic, this integration was exemplified by the WHO efforts in data dissemination and the subsequent global response. The role of public health informatics emerged as instrumental in this context, enhancing data collection, management, analysis, interpretation, and dissemination processes. A logic model for public health surveillance systems encapsulates the integration of these concepts. It outlines the inputs and outcomes and emphasizes the crucial actions and resources for effective system operation, including the imperative of training and capacity development.
{"title":"Brief Commentary: Using a Logic Model to Integrate Public Health Informatics Into Refinements of Public Health Surveillance System","authors":"GV Fant","doi":"10.5121/hiij.2024.13102","DOIUrl":"https://doi.org/10.5121/hiij.2024.13102","url":null,"abstract":"The COVID-19 pandemic has been a watershed moment in public health surveillance, highlighting the crucial role of data-driven insights in informing health actions and policies. Revisiting key concepts— public health, epidemiology in public health practice, public health surveillance, and public health informatics—lays the foundation for understanding how these elements converge to create a robust public health surveillance system framework. Especially during the COVID-19 pandemic, this integration was exemplified by the WHO efforts in data dissemination and the subsequent global response. The role of public health informatics emerged as instrumental in this context, enhancing data collection, management, analysis, interpretation, and dissemination processes. A logic model for public health surveillance systems encapsulates the integration of these concepts. It outlines the inputs and outcomes and emphasizes the crucial actions and resources for effective system operation, including the imperative of training and capacity development.","PeriodicalId":397015,"journal":{"name":"Health Informatics - An International Journal","volume":"5 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140418324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This review article examines the role of machine learning (ML) in enhancing Clinical Decision Support Systems (CDSSs) within the modern healthcare landscape. Focusing on the integration of various ML algorithms, such as regression, random forest, and neural networks, the review aims to showcase their potential in advancing patient care. A rapid review methodology was utilized, involving a survey of recent articles from PubMed and Google Scholar on ML applications in healthcare. Key findings include the demonstration of ML's predictive power in patient outcomes, its ability to augment clinician knowledge, and the effectiveness of ensemble algorithmic approaches. The review highlights specific applications of diverse ML models, including moment kernel machines in predicting surgical outcomes, k-means clustering in simplifying disease phenotypes, and extreme gradient boosting in estimating injury risk. Emphasizing the potential of ML to tackle current healthcare challenges, the article highlights the critical role of ML in evolving CDSSs for improved clinical decision-making and patient care. This comprehensive review also addresses the challenges and limitations of integrating ML into healthcare systems, advocating for a collaborative approach to refine these systems for safety, efficacy, and equity.
这篇综述文章探讨了机器学习（ML）在加强现代医疗保健领域临床决策支持系统（CDSS）方面的作用。文章重点关注回归、随机森林和神经网络等各种 ML 算法的整合，旨在展示它们在促进患者护理方面的潜力。我们采用了快速综述方法，包括对 PubMed 和谷歌学术中有关医疗保健领域应用 ML 的最新文章进行调查。主要研究结果包括证明了 ML 对患者预后的预测能力、增强临床医生知识的能力以及集合算法方法的有效性。综述重点介绍了各种 ML 模型的具体应用，包括矩核机在预测手术结果中的应用、k-均值聚类在简化疾病表型中的应用，以及极梯度提升在估计伤害风险中的应用。文章强调了 ML 在应对当前医疗保健挑战方面的潜力，强调了 ML 在发展 CDSS 以改善临床决策和患者护理方面的关键作用。这篇全面的综述还探讨了将 ML 整合到医疗保健系统中的挑战和局限性，提倡采用合作的方法来完善这些系统，以提高安全性、有效性和公平性。
{"title":"Integrating Machine Learning in Clinical Decision Support Systems","authors":"Tanay Subramanian","doi":"10.5121/hiij.2024.13101","DOIUrl":"https://doi.org/10.5121/hiij.2024.13101","url":null,"abstract":"This review article examines the role of machine learning (ML) in enhancing Clinical Decision Support Systems (CDSSs) within the modern healthcare landscape. Focusing on the integration of various ML algorithms, such as regression, random forest, and neural networks, the review aims to showcase their potential in advancing patient care. A rapid review methodology was utilized, involving a survey of recent articles from PubMed and Google Scholar on ML applications in healthcare. Key findings include the demonstration of ML's predictive power in patient outcomes, its ability to augment clinician knowledge, and the effectiveness of ensemble algorithmic approaches. The review highlights specific applications of diverse ML models, including moment kernel machines in predicting surgical outcomes, k-means clustering in simplifying disease phenotypes, and extreme gradient boosting in estimating injury risk. Emphasizing the potential of ML to tackle current healthcare challenges, the article highlights the critical role of ML in evolving CDSSs for improved clinical decision-making and patient care. This comprehensive review also addresses the challenges and limitations of integrating ML into healthcare systems, advocating for a collaborative approach to refine these systems for safety, efficacy, and equity.","PeriodicalId":397015,"journal":{"name":"Health Informatics - An International Journal","volume":"14 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140418910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Gulzar, Jiyun Li, Arslan Manzoor, Sadaf Rehmat, U. Amjad, H. Khan
In recent years, deep learning models have improved how well various diseases, particularly respiratory ailments, can be diagnosed. In order to assist in offering a diagnosis of respiratory pathologies in digitally recorded respiratory sounds, this research will provide an evaluation of the effectiveness of several deep learning models connected with the raw lung auscultation sounds in detecting respiratory pathologies. We will also determine which deep learning model is most appropriate for this purpose. With the development of computer -systems that can collect and analyze enormous volumes of data, the medical profession is establishing several non-invasive tools. This work attempts to develop a non-invasive technique for identifying respiratory sounds acquired by a stethoscope and voice recording software via machine learning techniques. This study suggests a trained and proven CNN-based approach for categorizing respiratory sounds. A visual representation of each audio sample is constructed, allowing resource identification for classification using methods like those used to effectively describe visuals. We used a technique called Mel Frequency Cepstral Coefficients (MFCCs). Here, features are retrieved and categorized via VGG16 (transfer learning) and prediction is accomplished using 5-fold cross-validation. Employing various data splitting techniques, Respiratory Sound Database obtained cutting-edge results, including accuracy of 95%, precision of 88%, recall score of 86%, and F1 score of 81 %. We trained and tested the model using a sound database made by the International Conference on Biomedical and Health Informatics (ICBHI) in 2017 and annotated by experts with a classification of the lung sound.
{"title":"DETECTION OF CRACKLES AND WHEEZES IN LUNG SOUND USING TRANSFER LEARNING","authors":"H. Gulzar, Jiyun Li, Arslan Manzoor, Sadaf Rehmat, U. Amjad, H. Khan","doi":"10.5121/hiij.2023.12201","DOIUrl":"https://doi.org/10.5121/hiij.2023.12201","url":null,"abstract":"In recent years, deep learning models have improved how well various diseases, particularly respiratory ailments, can be diagnosed. In order to assist in offering a diagnosis of respiratory pathologies in digitally recorded respiratory sounds, this research will provide an evaluation of the effectiveness of several deep learning models connected with the raw lung auscultation sounds in detecting respiratory pathologies. We will also determine which deep learning model is most appropriate for this purpose. With the development of computer -systems that can collect and analyze enormous volumes of data, the medical profession is establishing several non-invasive tools. This work attempts to develop a non-invasive technique for identifying respiratory sounds acquired by a stethoscope and voice recording software via machine learning techniques. This study suggests a trained and proven CNN-based approach for categorizing respiratory sounds. A visual representation of each audio sample is constructed, allowing resource identification for classification using methods like those used to effectively describe visuals. We used a technique called Mel Frequency Cepstral Coefficients (MFCCs). Here, features are retrieved and categorized via VGG16 (transfer learning) and prediction is accomplished using 5-fold cross-validation. Employing various data splitting techniques, Respiratory Sound Database obtained cutting-edge results, including accuracy of 95%, precision of 88%, recall score of 86%, and F1 score of 81 %. We trained and tested the model using a sound database made by the International Conference on Biomedical and Health Informatics (ICBHI) in 2017 and annotated by experts with a classification of the lung sound.","PeriodicalId":397015,"journal":{"name":"Health Informatics - An International Journal","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130278135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The study was conducted to identify some socioeconomic variables responsible for the prevalence of hypertensive kidney disease among Bangladeshi adults of 18 years and above. For this, 498 males and 497 females, totalling 995 adults of both urban and rural localities were investigated. In the sample there were 17.6% hypertensive adults and 18.9% of them were suffering from hypertension and kidney disease simultaneously. Beside other percentages of respondents, there were 19.6% elderly people of ages 50 years and above, 30.2% obese adults, 67.0% diabetic patients, 44.4% involved in sedentary activity and 33.1% smokers. The overall percentage of hypertensive kidney patients was 3.3. These group of patients were discriminated from the remaining 96.7% adults. During discrimination duration of diabetes was identified as most responsible variable followed by age, body mass index, sedentary activity, smoking habit, etc. The risk of prevalence of hypertensive kidney disease was 12.25 times in diabetic patients suffering for 15 years and above compared to the risk of prevalence in other adults. The risk was 8.43 times in elderly people, 16.80 times in obese adults, 2.50 times in adults involved in sedentary activity, and 1.91 times in smoker adults. Higher risk rate was also observed in adults of lower economic group of families.
{"title":"Identification of Socioeconomic Variables Responsible for Hypertensive Kidney Disease among Bangladeshi Adults","authors":"K. Bhuyan","doi":"10.5121/hiij.2023.12101","DOIUrl":"https://doi.org/10.5121/hiij.2023.12101","url":null,"abstract":"The study was conducted to identify some socioeconomic variables responsible for the prevalence of hypertensive kidney disease among Bangladeshi adults of 18 years and above. For this, 498 males and 497 females, totalling 995 adults of both urban and rural localities were investigated. In the sample there were 17.6% hypertensive adults and 18.9% of them were suffering from hypertension and kidney disease simultaneously. Beside other percentages of respondents, there were 19.6% elderly people of ages 50 years and above, 30.2% obese adults, 67.0% diabetic patients, 44.4% involved in sedentary activity and 33.1% smokers. The overall percentage of hypertensive kidney patients was 3.3. These group of patients were discriminated from the remaining 96.7% adults. During discrimination duration of diabetes was identified as most responsible variable followed by age, body mass index, sedentary activity, smoking habit, etc. The risk of prevalence of hypertensive kidney disease was 12.25 times in diabetic patients suffering for 15 years and above compared to the risk of prevalence in other adults. The risk was 8.43 times in elderly people, 16.80 times in obese adults, 2.50 times in adults involved in sedentary activity, and 1.91 times in smoker adults. Higher risk rate was also observed in adults of lower economic group of families.","PeriodicalId":397015,"journal":{"name":"Health Informatics - An International Journal","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124612553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The pharmacy profession is relatively new in China. Recently, the demand for pharmacists has increased as China's hospital system has been unable to support a large patient population due to the increasing demand for health care. This paper discusses how to improve the Chinese pharmacist law. To make reasonable laws on pharmacists, used to regulate and manage communication between pharmacists and patients, the ethical relationships, financial support and degree requirement, and governance of pharmacists. Improving pharmacist laws can help improve the quality of pharmacists' work, protect patient privacy, and enhance pharmacists' work efficiency. I will use government reports and authoritative data collected by myself as examples to analyze what needs to be improved in pharmacist law.
{"title":"Chinese Pharmacists Law Modification, How to Protect Patients‘ Interests？","authors":"Long-Fong Wang","doi":"10.5121/hiij.2022.11401","DOIUrl":"https://doi.org/10.5121/hiij.2022.11401","url":null,"abstract":"The pharmacy profession is relatively new in China. Recently, the demand for pharmacists has increased as China's hospital system has been unable to support a large patient population due to the increasing demand for health care. This paper discusses how to improve the Chinese pharmacist law. To make reasonable laws on pharmacists, used to regulate and manage communication between pharmacists and patients, the ethical relationships, financial support and degree requirement, and governance of pharmacists. Improving pharmacist laws can help improve the quality of pharmacists' work, protect patient privacy, and enhance pharmacists' work efficiency. I will use government reports and authoritative data collected by myself as examples to analyze what needs to be improved in pharmacist law.","PeriodicalId":397015,"journal":{"name":"Health Informatics - An International Journal","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120955397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pediatric home accidents still a nightmare for parents, especially for who don’t know how to act in such situations. With the digital health advancements, it will be possible to avoid the disasters of these accidents, especially falls. In this paper, we will present the definition of each of home accidents and ehealth, the motivations and the challenges of this work, related works and propose a prototype to avoid falls disasters with a discussion of the positive and negative points of this prototype and finally make a comparison between our approach and the related works.
{"title":"E-Health Preventing Pediatric Home Accidents","authors":"Chiraz Bouderbali, Ghalem Belalem","doi":"10.5121/hiij.2022.11301","DOIUrl":"https://doi.org/10.5121/hiij.2022.11301","url":null,"abstract":"Pediatric home accidents still a nightmare for parents, especially for who don’t know how to act in such situations. With the digital health advancements, it will be possible to avoid the disasters of these accidents, especially falls. In this paper, we will present the definition of each of home accidents and ehealth, the motivations and the challenges of this work, related works and propose a prototype to avoid falls disasters with a discussion of the positive and negative points of this prototype and finally make a comparison between our approach and the related works.","PeriodicalId":397015,"journal":{"name":"Health Informatics - An International Journal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130481760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A large number of annotation systems in e-health domain have been implemented in the literature. Several factors distinguish these systems from one another. In fact, each of these systems is based on a separate paradigm, resulting in a disorganized and unstructured vision. As part of our research, we attempted to categorize them based on the functionalities provided by each system, and we also proposed a model of annotations that integrates both the health professional and the patient in the process of annotating the medical file.
{"title":"Towards a Standard of Modelling Annotations in the E-Health Domain","authors":"Zayneb Mannai, Anis Kalboussi, A. Hadj Kacem","doi":"10.5121/hiij.2021.10401","DOIUrl":"https://doi.org/10.5121/hiij.2021.10401","url":null,"abstract":"A large number of annotation systems in e-health domain have been implemented in the literature. Several factors distinguish these systems from one another. In fact, each of these systems is based on a separate paradigm, resulting in a disorganized and unstructured vision. As part of our research, we attempted to categorize them based on the functionalities provided by each system, and we also proposed a model of annotations that integrates both the health professional and the patient in the process of annotating the medical file.","PeriodicalId":397015,"journal":{"name":"Health Informatics - An International Journal","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127500737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The use of lasers has evolved as clinical experience along with scientific investigation. The dental lasers of today have benefited from decades of laser research and have their basis in certain theories from the field of quantum mechanics. When used efficaciously and ethically, lasers are an exceptional modality of treatment for many clinical conditions that dental specialists treat on a daily basis. The concept of using lasers for the treatment of periodontal disease elicits very strong reactions from all sides of spectrum. Evidence suggests that lasers are useful as an adjunct or alternative to traditional approaches in periodontal therapy. Future direction of lasers would be towards a minimally invasive regenerative procedures along with laser assisted calculus detection systems using laser fluorescence that is optical coherence tomography and a laser system which selectively and completely removes the plaque and calculus that is under development. With recent advances and development of wide range of laser wavelengths, different instrument designs and different delivery systems, the purpose of this review is to determine the application and current concept of lasers in the regeneration of periodontal tissues.
{"title":"Lasers – It’s Role in Periodontal Regeneration","authors":"Princy Anna Mathew, V. More, Jagadish Pai B.S","doi":"10.5121/hiij.2018.7401","DOIUrl":"https://doi.org/10.5121/hiij.2018.7401","url":null,"abstract":"The use of lasers has evolved as clinical experience along with scientific investigation. The dental lasers of today have benefited from decades of laser research and have their basis in certain theories from the field of quantum mechanics. When used efficaciously and ethically, lasers are an exceptional modality of treatment for many clinical conditions that dental specialists treat on a daily basis. The concept of using lasers for the treatment of periodontal disease elicits very strong reactions from all sides of spectrum. Evidence suggests that lasers are useful as an adjunct or alternative to traditional approaches in periodontal therapy. Future direction of lasers would be towards a minimally invasive regenerative procedures along with laser assisted calculus detection systems using laser fluorescence that is optical coherence tomography and a laser system which selectively and completely removes the plaque and calculus that is under development. With recent advances and development of wide range of laser wavelengths, different instrument designs and different delivery systems, the purpose of this review is to determine the application and current concept of lasers in the regeneration of periodontal tissues.","PeriodicalId":397015,"journal":{"name":"Health Informatics - An International Journal","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124630510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Semwanga, H. Namatovu, Swaib Kyanda Kaawaase, M. Magumba
There is growing interest in the rate of eHealth uptake resulting from the increased potential to advance the quality of healthcare services in both the developed and developing countries. Although the implementation of information and communication technology to support healthcare delivery would greatly address the quality and accessibility challenges in healthcare as well as reduction in the cost of healthcare delivery, the adoption of eHealth has not been fully realized. This study aimed at conducting a systematic literature review to establish the factors associated with the adoption of eHealth and propose a context-specific framework for successful adoption of eHealth technologies in developing countries such as Uganda. The systematic literature review process was guided by the Systematic Review Protocol. The review of 29 journals from the period 2009-2021 showed that, although the most widely used frameworks in the developing countries were Technology Adoption Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT) framework and Technology Organization Environment (TOE) framework, there were other salient factors reported by other researchers that contributed to the adoption of eHealth in developing countries. A novel framework for adoption of eHealth in the local context with eight (8) dimensions namely; Socio-demographic, Technology, Information, Socio-cultural, Organization, Governance, Ethical and legal and Financial dimensions is derived and presented as result of the research.
{"title":"An EHealth Adoption Framework for Developing Countries: A Systematic Review","authors":"A. Semwanga, H. Namatovu, Swaib Kyanda Kaawaase, M. Magumba","doi":"10.5121/hiij.2021.10301","DOIUrl":"https://doi.org/10.5121/hiij.2021.10301","url":null,"abstract":"There is growing interest in the rate of eHealth uptake resulting from the increased potential to advance the quality of healthcare services in both the developed and developing countries. Although the implementation of information and communication technology to support healthcare delivery would greatly address the quality and accessibility challenges in healthcare as well as reduction in the cost of healthcare delivery, the adoption of eHealth has not been fully realized. This study aimed at conducting a systematic literature review to establish the factors associated with the adoption of eHealth and propose a context-specific framework for successful adoption of eHealth technologies in developing countries such as Uganda. The systematic literature review process was guided by the Systematic Review Protocol. The review of 29 journals from the period 2009-2021 showed that, although the most widely used frameworks in the developing countries were Technology Adoption Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT) framework and Technology Organization Environment (TOE) framework, there were other salient factors reported by other researchers that contributed to the adoption of eHealth in developing countries. A novel framework for adoption of eHealth in the local context with eight (8) dimensions namely; Socio-demographic, Technology, Information, Socio-cultural, Organization, Governance, Ethical and legal and Financial dimensions is derived and presented as result of the research.","PeriodicalId":397015,"journal":{"name":"Health Informatics - An International Journal","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129669611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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