Clinical eHealth最新文献

{"title":"Editorials: Inactivated vaccines protection against COVID-19 symptomatic infections","authors":"Yifan Chen","doi":"10.1016/j.ceh.2023.04.001","DOIUrl":"https://doi.org/10.1016/j.ceh.2023.04.001","url":null,"abstract":"<div><p>Omicron variants of SARS-CoV-2 have been become the dominant variant family among more than 100 countries and regions around the world. There are still limited data on how inactivated COVID-19 vaccines prevent Omicron-related symptomatic infection, transmission, hospital admission, and death3. Recently, Dawei Yang et al. published a paper in the to explore the effect of inactivated COVID-19 vaccines on Omicron from the perspective of real-world observation data.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"6 ","pages":"Pages 1-2"},"PeriodicalIF":0.0,"publicationDate":"2023-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49711745","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}

{"title":"Expert consensus on the metaverse in medicine","authors":"Dawei Yang ,&nbsp;Jian Zhou ,&nbsp;Rongchang Chen ,&nbsp;Yuanlin Song ,&nbsp;Zhenju Song ,&nbsp;Xiaoju Zhang ,&nbsp;Qi Wang ,&nbsp;Kai Wang ,&nbsp;Chengzhi Zhou ,&nbsp;Jiayuan Sun ,&nbsp;Lichuan Zhang ,&nbsp;Li Bai ,&nbsp;Yuehong Wang ,&nbsp;Xu Wang ,&nbsp;Yeting Lu ,&nbsp;Hongyi Xin ,&nbsp;Charles A. Powell ,&nbsp;Christoph Thüemmler ,&nbsp;Niels H. Chavannes ,&nbsp;Wei Chen ,&nbsp;Chunxue Bai","doi":"10.1016/j.ceh.2022.02.001","DOIUrl":"https://doi.org/10.1016/j.ceh.2022.02.001","url":null,"abstract":"<div><h3>Background</h3><p>Recently, Professor Chunxue Bai and colleagues have proposed a definition of the Metaverse in Medicine as the medical Internet of Things (MIoT) facilitated using AR and/or VR glasses.</p></div><div><h3>Methods</h3><p>A multi-disciplinary panel of doctors and IT experts from Asia, the United States, and Europe analyzed published articles regarding expert consensus on the Medical Internet of Things, with reference to study results in the field of metaverse technology.</p></div><div><h3>Findings</h3><p>It is feasible to implement the three basic functions of the MIoT, namely, comprehensive perception, reliable transmission, and intelligent processing, by applying a metaverse platform, which is composed of AR and VR glasses and the MIoT system, and integrated with the technologies of holographic construction, holographic emulation, virtuality-reality integration, and virtuality-reality interconnection. In other words, through interactions between virtual and real cloud experts and terminal doctors, we will be able to carry out medical education, science popularization, consultation, graded diagnosis and treatment, clinical research, and even comprehensive healthcare in the metaverse. The interaction between virtual and real cloud experts and terminal users (including terminal doctors, patients, and even their family members) could also facilitate different medical services, such as disease prevention, healthcare, physical examination, diagnosis and treatment of diseases, rehabilitation, management of chronic diseases, in-home care, first aid, outpatient attendance, consultation, etc. In addition, it is noteworthy that security is a prerequisite for the Metaverse in Medicine, and a reliable security system is the foundation to ensure the normal operation of such a platform.</p></div><div><h3>Conclusion</h3><p>The application of a Cloud Plus Terminal platform could enable interaction between virtual and real cloud experts and terminal doctors, in order to realize medical education, science popularization, consultation, graded diagnosis and treatment, clinical research, and even comprehensive healthcare in the metaverse.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"5 ","pages":"Pages 1-9"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914122000016/pdfft?md5=61d0425834eefff75dea23f73f0c19d9&pid=1-s2.0-S2588914122000016-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91764416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A large-scale clinical validation study using nCapp cloud plus terminal by frontline doctors for the rapid diagnosis of COVID-19 and COVID-19 pneumonia in China","authors":"Dawei Yang ,&nbsp;Tao Xu ,&nbsp;Xun Wang ,&nbsp;Deng Chen ,&nbsp;Ziqiang Zhang ,&nbsp;Lichuan Zhang ,&nbsp;Jie Liu ,&nbsp;Kui Xiao ,&nbsp;Li Bai ,&nbsp;Yong Zhang ,&nbsp;Lin Zhao ,&nbsp;Lin Tong ,&nbsp;Chaomin Wu ,&nbsp;Yaoli Wang ,&nbsp;Chunling Dong ,&nbsp;Maosong Ye ,&nbsp;Yu Xu ,&nbsp;Zhenju Song ,&nbsp;Hong Chen ,&nbsp;Jing Li ,&nbsp;Chunxue Bai","doi":"10.1016/j.ceh.2022.07.004","DOIUrl":"https://doi.org/10.1016/j.ceh.2022.07.004","url":null,"abstract":"<div><h3>Background</h3><p>The outbreak of coronavirus disease 2019 (COVID-19) has become a global pandemic acute infectious disease, especially with the features of possible asymptomatic carriers and high contagiousness. Currently, it is difficult to quickly identify asymptomatic cases or COVID-19 patients with pneumonia due to limited access to reverse transcription-polymerase chain reaction (RT-PCR) nucleic acid tests and CT scans.</p></div><div><h3>Goal</h3><p>This study aimed to develop a scientific and rigorous clinical diagnostic tool for the rapid prediction of COVID-19 cases based on a COVID-19 clinical case database in China, and to assist doctors to efficiently and precisely diagnose asymptomatic COVID-19 patients and cases who had a false-negative RT-PCR test result.</p></div><div><h3>Methods</h3><p>With online consent, and the approval of the ethics committee of Zhongshan Hospital Fudan University (NCT04275947, B2020-032R) to ensure that patient privacy is protected, clinical information has been uploaded in real-time through the New Coronavirus Intelligent Auto-diagnostic Assistant Application of cloud plus terminal (nCapp) by doctors from different cities (Wuhan, Shanghai, Harbin, Dalian, Wuxi, Qingdao, Rizhao, and Bengbu) during the COVID-19 outbreak in China. By quality control and data anonymization on the platform, a total of 3,249 cases from COVID-19 high-risk groups were collected. The effects of different diagnostic factors were ranked based on the results from a single factor analysis, with 0.05 as the significance level for factor inclusion and 0.1 as the significance level for factor exclusion. Independent variables were selected by the step-forward multivariate logistic regression analysis to obtain the probability model.</p></div><div><h3>Findings</h3><p>We applied the statistical method of a multivariate regression model to the training dataset (1,624 cases) and developed a prediction model for COVID-19 with 9 clinical indicators that are accessible. The area under the receiver operating characteristic (ROC) curve (AUC) for the model was 0.88 (95% CI: 0.86, 0.89) in the training dataset and 0.84 (95% CI: 0.82, 0.86) in the validation dataset (1,625 cases).</p></div><div><h3>Discussion</h3><p>With the assistance of nCapp, a mobile-based diagnostic tool developed from a large database that we collected from COVID-19 high-risk groups in China, frontline doctors can rapidly identify asymptomatic patients and avoid misdiagnoses of cases with false-negative RT-PCR results.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"5 ","pages":"Pages 79-90"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914122000193/pdfft?md5=02394802925daa4218c01fe3c828ae4d&pid=1-s2.0-S2588914122000193-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91680434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The influence of telemedicine on capacity development in public primary hospitals in China: A scoping review","authors":"Junyue Zhang ,&nbsp;Qingjun Lu ,&nbsp;Leiyu Shi","doi":"10.1016/j.ceh.2022.10.001","DOIUrl":"10.1016/j.ceh.2022.10.001","url":null,"abstract":"<div><p>With the rapid development of telemedicine equipment and information communication technology, telemedicine has developed rapidly and is used widely around the world as a new mode of medical service. This new technology has been used widely in China and has benefited a large number of patients. Due to the hospital-centric structure in health sector, resources and patients became increasingly concentrated in hospitals instead of primary care. In this way, telemedicine is a crucial method for government to the inequality of medical resources between urban and rural areas. But little is known about the influence of telemedicine on public primary hospitals in China. The objective of this study is to review the influence of telemedicine on capacity development of respiratory department in public primary hospital in China. A scoping review was conducted using electronic databases including PubMed, Cochrane Library, EMBASE and Google Scholar. Telemedicine has a major impact on the establishment of a complete national health system. The immediate sharing of medical information effectively alleviates the situation of serious information imbalance between doctors and patients. It also guides the public to make rational choice of medical behaviour. In public emergencies, telemedicine can quickly concentrate all kinds of high-quality medical resources to the sites, ensure the safety of people's lives, and provide effective rescue and treatment for the wounded in various special environments. It is conducive to giving full play to the market competition value of public hospital reputation, encouraging hospitals to continuously improve medical technology level, improving medical service quality, actively taking social medical and health responsibility, and this could promote the overall medical and health capacities development.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"5 ","pages":"Pages 91-99"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914122000211/pdfft?md5=fcfda809112a72d013315debc7003934&pid=1-s2.0-S2588914122000211-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82578998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A 68-year-old female with pulmonary nodules harboring 341 circulating abnormal cells","authors":"Lu Wang ,&nbsp;Dawei Yang ,&nbsp;Lin Tong ,&nbsp;Yuanlin Song ,&nbsp;Chunxue Bai","doi":"10.1016/j.ceh.2022.11.002","DOIUrl":"https://doi.org/10.1016/j.ceh.2022.11.002","url":null,"abstract":"<div><h3>Background</h3><p>Early diagnosis and treatment are key to improving survival and prognosis of patients with lung cancer. Liquid biopsy and artificial intelligence (AI) can help diagnose early lung cancer.</p></div><div><h3>Case presentation</h3><p>We present a 68-year-old female with a family history of pulmonary nodules without smoking history who found multiple nodules in the lungs on physical examination. Malignant lung nodules were diagnosed based on AI evaluation and 341 circulating abnormal cells (CACs). Surgical resection confirmed the diagnosis of pulmonary adenocarcinoma and the CACs decreased to 151 at postoperative follow-up in one month and to 54 six months after surgery.</p></div><div><h3>Conclusion</h3><p>CACs helps to improve the accuracy of AI diagnosis of early lung cancer and the prognosis of patients with lung cancer at follow-up.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"5 ","pages":"Pages 106-108"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914122000235/pdfft?md5=322f2f3960ff36345eb5ae3995007457&pid=1-s2.0-S2588914122000235-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90015474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metaverse in medicine","authors":"Dawei Yang ,&nbsp;Jian Zhou ,&nbsp;Yuanlin Song ,&nbsp;Mengting Sun ,&nbsp;Chunxue Bai","doi":"10.1016/j.ceh.2022.04.002","DOIUrl":"https://doi.org/10.1016/j.ceh.2022.04.002","url":null,"abstract":"<div><p>The emergence of the Medical Internet of Things (MIoT) has presented an opportune solution to these problems, as it provides effective technological support. Based on the current MIoT theory, it is feasible to realize efficient and accurate graded diagnosis and treatment through the linkage between doctors in large hospitals (the ‘Cloud Experts’) and doctors in small hospitals (the ‘Terminal Doctors’), and to contribute to the research and development of related technologies to improve graded diagnosis and treatment in China. Nevertheless, the following issues remain in clinical practice: (1) The Cloud Experts are not available to dedicate themselves to popular science education, or to give professional lectures, at all times and in all settings. (2) The Cloud Experts are not available to provide guidance for the Terminal Doctors on diagnosis and treatment at all times and in all settings. (3) In clinical trials, the main researchers are not available to monitor the research or guide the team at all times and in all settings. (4) Due to the lack of real-time quality control at all times and in all settings, non-standard diagnosis and treatment, with the features of a handicraft workshop, still exist to a considerable degree. The real cause lies in the limitations of the Internet technology itself, which cannot facilitate communication at all times and in all settings between the Cloud Experts and the Terminal Doctors involved in graded diagnosis and treatment. Therefore, the MIoT-based digital platforms need to be further improved, especially concerning the communication and interactions between humans and computers, and the integration and linkage between the virtual and real worlds. It is gratifying that the concept of the metaverse has been introduced, which provides a possible solution to all these problems, and serves as a foundation for the proposal and development of the Metaverse in Medicine.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"5 ","pages":"Pages 39-43"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914122000132/pdfft?md5=780094def26bd54abc05aa228daf1d4c&pid=1-s2.0-S2588914122000132-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91764413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emerging artificial intelligence methods for fighting lung cancer: A survey","authors":"Jieli Zhou,&nbsp;Hongyi Xin","doi":"10.1016/j.ceh.2022.04.001","DOIUrl":"https://doi.org/10.1016/j.ceh.2022.04.001","url":null,"abstract":"<div><p>Lung cancer has one of the highest incidence rates and mortality rates among all common cancers worldwide. Early detection of suspicious lung nodules is crucial in fighting lung cancer. In recent years, with the proliferation of clinical data like low-dose computed tomography (LDCT), histology whole slide images, electronic health records, and sensor readings from medical IoT devices etc., many artificial intelligence tools have taken more important roles in lung cancer management. In this survey, we lay out the current and emergent artificial intelligence methods for fighting lung cancers. Besides the commonly used CT image based deep learning models for detecting and diagnosing lung nodules, we also cover emergent AI techniques for lung cancer: 1) <strong>federated deep learning models</strong> for harnessing multi-center data with privacy in mind, 2) <strong>multi-modal deep learning models</strong> for integrating multiple sources of clinical and image data, 3) <strong>interpretable deep learning models</strong> for opening the black box for clinicians. In the big data era for cancer management, we believe this short survey will help AI researchers better understand the clinical challenges of lung cancer and will also help clinicians better understand the emergent AI tools.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"5 ","pages":"Pages 19-34"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914122000119/pdfft?md5=0894d8f224ef6121ffb0ef3a06ce63a7&pid=1-s2.0-S2588914122000119-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91724731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Professor Bai Chunxue and Associate Research Yang Dawei of the Engineering Center shared the latest achievements of China LCBP study at the Joint Conference of the 26th Congress of Asia Pacific Society of Respirology (APSR) and World Health Organization (WHO) Big 5 Lung Diseases Workshop held in Seoul, Republic of Korea in 2022","authors":"Mengting Sun ,&nbsp;Dawei Yang ,&nbsp;Jian Zhou ,&nbsp;Chunxue Bai","doi":"10.1016/j.ceh.2022.11.003","DOIUrl":"https://doi.org/10.1016/j.ceh.2022.11.003","url":null,"abstract":"","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"5 ","pages":"Pages 117-122"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914122000247/pdfft?md5=1aeeb84bbadb88c1211338e8abc35fca&pid=1-s2.0-S2588914122000247-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90015475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preliminary effects of a digital mental health intervention for depression and anxiety","authors":"Mirjam L. van Orden ,&nbsp;Jan C. Kraaijeveld ,&nbsp;Annet T. Spijker ,&nbsp;Anna V. Silven ,&nbsp;Tobias N. Bonten ,&nbsp;Niels H. Chavannes ,&nbsp;Annemiek van Dijke","doi":"10.1016/j.ceh.2022.06.002","DOIUrl":"https://doi.org/10.1016/j.ceh.2022.06.002","url":null,"abstract":"<div><h3>Background</h3><p>Digital mental healthcare interventions (DMHIs) have been repeatedly mentioned as a possible solution for the growing demand for accessible treatment for patients suffering from common mental health problems, i.e. depression and anxiety disorders. However, structural implementation of DMHI is sparse and results on outcome seems inconclusive. To enrich the body of evidence, this paper compares a need-driven digital mental healthcare intervention (DMHI) for patients diagnosed with depression or anxiety disorders with traditional face-to-face treatment. The digital treatment is provided using a smartphone app which provides videoconferencing, chat, calendar- and registration functions.</p></div><div><h3>Method</h3><p>In a naturalistic retrospective cohort study patients who received DMHI are compared to patients who received traditional face-to-face treatment. Furthermore three illustrative cases were selected to demonstrate how personalization is expressed in individual treatments.</p></div><div><h3>Results</h3><p>The first results of the DMHI compare favorably with traditional face-to-face treatment, showing comparable satisfaction rates, equal effectiveness, and a significant decrease in treatment duration in weeks.</p></div><div><h3>Conclusion</h3><p>The DMHI has the potential to be as effective, but more efficient than traditional face-to-face treatment. Furthermore the digital treatment opens up options to fine-tune the frequency, duration, and content of care contacts to align with patients' individual situations and personal preferences.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"5 ","pages":"Pages 44-51"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914122000156/pdfft?md5=143e6fbdff30a74d7274c32e2b41316f&pid=1-s2.0-S2588914122000156-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90028199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chinese expert consensus on the application of the Internet of Things as assistive technology for the diagnosis and treatment of acute asthma exacerbations","authors":"Xueling Wu ,&nbsp;Zhenju Song ,&nbsp;Fanglei Liu ,&nbsp;Chunxue Bai ,&nbsp;Clinical eHealth Chinese expert group on the IoT-assisted diagnosis and treatment of acute asthma exacerbations","doi":"10.1016/j.ceh.2022.12.002","DOIUrl":"https://doi.org/10.1016/j.ceh.2022.12.002","url":null,"abstract":"","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"5 ","pages":"Pages 109-116"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914122000260/pdfft?md5=bb42b0ecfe88fe444104e49b8f40001f&pid=1-s2.0-S2588914122000260-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90028200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}