Clinical eHealth最新文献

{"title":"Wearable dynamic electrocardiogram monitor-based screening for atrial fibrillation in the community-dwelling elderly population","authors":"Lili Wei ,&nbsp;Enyong Su ,&nbsp;Jianfang Xie ,&nbsp;Wangqiong Xiong ,&nbsp;Xiaoyue Song ,&nbsp;Junqiang Xue ,&nbsp;Chunyu Zhang ,&nbsp;Ying Hu ,&nbsp;Peng Yu ,&nbsp;Ming Liu ,&nbsp;Hong Jiang","doi":"10.1016/j.ceh.2024.03.001","DOIUrl":"https://doi.org/10.1016/j.ceh.2024.03.001","url":null,"abstract":"<div><h3>Background</h3><p>Atrial fibrillation (AF) is a major public health problem with high rates of morbidity, disability and mortality, especially in the elderly population. This study explored the diagnosis and treatment status of AF in adults aged ≥65 years in the community through wearable dynamic electrocardiogram (ECG) monitoring.</p></div><div><h3>Methods</h3><p>We conducted a cross-sectional study in 4 random communities within the Qingpu district of Shanghai, China. Between January 1, 2020 and June 30, 2022, the ECGs of 3852 adults aged 65 years or older were examined through wearable dynamic ECG monitoring. Data from 3839 participants were ultimately analyzed. Multivariate logistic regression was used to determine the independent predictors of AF.</p></div><div><h3>Results</h3><p>Wearable dynamic ECG monitoring detected AF in 360 elderly people, 78 of whom were diagnosed with AF for the first time. Multivariate logistic regression analysis revealed that snoring, renal dysfunction, coronary heart disease and high CHA2DS2-VASc score were independent risk factors for AF. Among patients with unknown AF, 68 (87.20 %) met the criteria for anticoagulant therapy based on the CHA2DS2-VASc score. Only 4 (5.88 %) patients were taking anticoagulants. Of the patients with a clear history of AF, 249 (84.98 %) needed an anticoagulant strategy, but only 18 (7.23 %) took oral anticoagulants.</p></div><div><h3>Conclusion</h3><p>Many elderly people have silent AF, and wearable dynamic ECG monitoring can be used to screen for AF effectively.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"7 ","pages":"Pages 41-50"},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914124000042/pdfft?md5=72112205cb77141c5cc6cc24e5e597f3&pid=1-s2.0-S2588914124000042-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140133905","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":"Expert consensus on the evaluation and management of high-risk indeterminate pulmonary nodules","authors":"Yang Dawei ,&nbsp;Stephan Lam ,&nbsp;Kai Wang ,&nbsp;Zhou Jian ,&nbsp;Zhang Xiaoju ,&nbsp;Wang Qi ,&nbsp;Zhou Chengzhi ,&nbsp;Zhang Lichuan ,&nbsp;Bai Li ,&nbsp;Wang Yuehong ,&nbsp;Li Ming ,&nbsp;Sun Jiayuan ,&nbsp;Li Yang ,&nbsp;Fengming Kong ,&nbsp;Haiquan Chen ,&nbsp;Ming Fan ,&nbsp;Xuan Jianwei ,&nbsp;Fred R. Hirsch ,&nbsp;Charles A. Powell ,&nbsp;Bai Chunxue","doi":"10.1016/j.ceh.2024.01.002","DOIUrl":"10.1016/j.ceh.2024.01.002","url":null,"abstract":"<div><h3>Background</h3><p>The most effective method for improving the prognosis of lung cancer is the application of low-dose computed tomography (LDCT) for pulmonary nodule screening in populations at high risk. Timely diagnosis and treatment of early-stage lung cancer can contribute to higher long-term survival rates. However, it remains difficult to differentiate malignant from benign pulmonary nodules measuring 8–15 mm, and avoid overtreatment on the one hand and delayed diagnosis on the other hand. In this consensus paper, we aimed to clarify the definition of “high-risk indeterminate pulmonary nodules (IPNs)” and discuss appropriate evaluation and management to facilitate timely diagnosis of lung cancer to improve lung cancer outcome. Direction for future research was discussed.</p></div><div><h3>Methods</h3><p>A multi-disciplinary panel of doctors and IT experts from Asia, Canada and the U.S. were invited to participate. Published evidence and consensus guidelines were used to develop this consensus was clarified. Their evaluation and management were discussed.</p></div><div><h3>Findings</h3><p>The experts believed that the prevalence of pulmonary nodules was very high, and it that was difficult to diagnose early-stage lung cancer due to the small size of the nodules, often leading to delayed diagnosis or overtreatment. To address this issue and to improve long-term outcome, the panel considered important to revise the classification of high-risk IPNs, (1) as pulmonary nodules that cannot be clearly diagnosed with non-surgical biopsy procedures, but is highly suspicious for early-stage lung cancer. The panel also recommends the most responsible should arrange imaging evaluations and follow-ups, taking new technologies into account. Artificial intelligence (AI) assessment based on the Medical Internet of Things (MIoT) can be combined with expert opinion to form a human–computer multidisciplinary team (MDT) that can fully implement the three core procedures of the MIoT, namely, comprehensive perception, reliable transmission, and intelligent processing. This will help to upgrade the non-standard diagnosis and treatment, the so-called “handicraft workshop model”, to a modern assembly-line model that meets international standards. The MIoT technology, which has the potential to realize “simplification of complex problems, digitalization of simple problems, programming of digital problems, and systematization of programming problems”, can promote the homogeneous evaluation of pulmonary nodules by enhancing both the sensitivity and the specificity of detecting early-stage lung cancer, in order to avoid delayed diagnosis and overtreatment.</p></div><div><h3>Conclusion</h3><p>To optimize the evaluation of early-stage lung cancer, and to avoid delayed diagnosis and overtreatment, it is necessary to propose and promote the concept of “high-risk IPNs”. The application of current technologies, AI, and a human–computer MDT, will facilitate improvement","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"7 ","pages":"Pages 27-35"},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914124000029/pdfft?md5=4d48face93be68b92a61a9b7ba6d57cd&pid=1-s2.0-S2588914124000029-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139634147","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":"Wearable electronic devices in the intensive care units","authors":"Jiahuan Chen ,&nbsp;Weipeng Jiang ,&nbsp;Yuanlin Song","doi":"10.1016/j.ceh.2024.02.001","DOIUrl":"https://doi.org/10.1016/j.ceh.2024.02.001","url":null,"abstract":"<div><p>In the realm of intensive care medicine, wearable electronic devices have emerged as a highly promising field, driven by advancements in mobile, intelligent, and personalized healthcare. They are defined as devices that can be worn directly on the body, offering portable services by actively recording physiological parameters and metabolic status, providing index monitoring, clinical diagnosis, and disease treatment. This review specifically highlights the utilization of wearable devices in intensive care units within the field of intensive care medicine, anticipating their future applications.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"7 ","pages":"Pages 36-40"},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914124000030/pdfft?md5=625cd71e8917a386f340f2899a6a2814&pid=1-s2.0-S2588914124000030-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140103390","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":"Hybrid approach of type-2 fuzzy inference system and PSO in asthma disease","authors":"Tarun Kumar ,&nbsp;Anirudh Kumar Bhargava ,&nbsp;M.K. Sharma ,&nbsp;Nitesh Dhiman ,&nbsp;Neha Nain","doi":"10.1016/j.ceh.2024.01.001","DOIUrl":"10.1016/j.ceh.2024.01.001","url":null,"abstract":"<div><p>This research work presents a hybrid approach combining a type-2 fuzzy inference system with particle swarm optimization (PSO) to develop a type-2 fuzzy optimized inference system, specifically tailored for asthma patient data. Addressing the inherent uncertainty in medical diagnostics, this model enhances traditional type-1 fuzzy logic by incorporating ambiguity into linguistic variables and utilizing type-2 fuzzy if-then rules. The system is trained to minimize diagnostic error in asthma disease identification. Applied to a dataset comprising eight medical entities from asthma patients, the model demonstrates substantial accuracy improvements. Numerical computations validate the system, showing a decrease in error rate from 1.445 to 0.03, indicating a significant enhancement in diagnostic precision. These results underscore the potential of our model in medical diagnostic problems, providing a novel and effective tool for tackling the complexities of asthma diagnosis.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"7 ","pages":"Pages 15-26"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914124000017/pdfft?md5=305cae56b1c8d6a5f0ff62a1ec33c6ad&pid=1-s2.0-S2588914124000017-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139454813","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":"Post pandemic analysis on comprehensive utilization of telehealth and telemedicine","authors":"Hamunyare Ndwabe,&nbsp;Arindam Basu,&nbsp;Jalal Mohammed","doi":"10.1016/j.ceh.2023.12.002","DOIUrl":"10.1016/j.ceh.2023.12.002","url":null,"abstract":"<div><p>The existing global health crisis characterized by limited resources, including health personnel, has prompted the adoption of telemedicine and telehealth, especially in the post-pandemic era. The COVID-19 pandemic accelerated the adoption of these technologies, and as the world navigates beyond the crisis, it is essential to assess the extent of utilization of telehealth and telemedicine. This review study aims to assess the extent to which teleservices have been implemented worldwide across different continents. Peer-reviewed telehealth and telemedicine articles were reviewed across Web of Science, Scopus, Cochrane Library and Pubmed/Medline databases. The exclusion criteria comprised all articles published before 1 December 2019, any other databases, duplicates, and grey literature. The inclusion criteria for this study encompassed articles published on or after December 1, 2019. This timeframe allowed us to focus on the pandemic and post-pandemic era. A total of 381 publications were identified for inclusion, which were screened based on reviewing the titles, abstracts and full-text content down to 102 relevant articles. Utilization trends were identified amongst the different countries across the continents, and these were classified into advanced, developed, developing and emerging adoption stages. The respective characteristics utilized in differentiating these adoption stages were identified, encompassing the inclusivity of teleservices in administration, disease diagnosis, treatment, patient follow-ups, pharmacy services and electronic health records transversely. According to this review, of the countries surveyed (n = 77), (n = 27) 13.8 % are at an advanced adoption stage, (n = 20) 10.3 % are at a developed level, (n = 24) 12.3 % are at the developed stage, and (n = 6) 3 % are at the emerging stage, as percentages of all the countries in the world (N = 195). In conclusion, this study demonstrated the extent to which various nations have adopted telehealth and telemedicine from the onset of the COVID-19 pandemic to 2023.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"7 ","pages":"Pages 5-14"},"PeriodicalIF":0.0,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914123000333/pdfft?md5=a0a94050b8b44a3dbfbfe4413e437bb3&pid=1-s2.0-S2588914123000333-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138620282","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":"Research progress of MIoT and digital healthcare in the new era","authors":"Peizhi Tao,&nbsp;Na Liu,&nbsp;Chunling Dong","doi":"10.1016/j.ceh.2023.11.004","DOIUrl":"10.1016/j.ceh.2023.11.004","url":null,"abstract":"<div><p>Medical Internet of Things (MIoT) and Digital healthcare have long since ceased to be separate entities. Cross-fertilisation of MIoT-based digital medical treatment models is the way forward. However, few studies discuss the development of MIoT and Digital healthcare in clinical practice. This paper reviews the research progress of MIoT and Digital healthcare in related fields.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"7 ","pages":"Pages 1-4"},"PeriodicalIF":0.0,"publicationDate":"2023-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914123000308/pdfft?md5=28379662e4cbb2b3648c5e3750e1dc67&pid=1-s2.0-S2588914123000308-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138612265","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":"Concept and prospect of the Human-Computer Multi-Disciplinary team (MDT) in pulmonary nodule evaluation","authors":"Li Yang ,&nbsp;Dawei Yang ,&nbsp;Man yao ,&nbsp;Chunxue Bai","doi":"10.1016/j.ceh.2023.11.003","DOIUrl":"10.1016/j.ceh.2023.11.003","url":null,"abstract":"<div><p>Lung cancer is the leading cause of cancer-related deaths worldwide. Early diagnosis and treatment play a crucial role in improving the prognosis for lung cancer. However, the issue of overtreatment and delayed diagnosis remains prevalent due to the considerable limitations of manual film review in facilitating early detection and treatment of lung cancer. In recent years, artificial intelligence (AI) has emerged as a valuable tool for clinicians to screen and evaluate benign and malignant pulmonary nodules, offering numerous advantages. Nevertheless, the sensitivity and specificity of AI are neither sufficient to completely replace medical experts nor capable of assuming direct responsibility for clinical diagnosis and treatment.</p><p>Therefore, we propose the concept of a Human-Computer Multi-Disciplinary Team (MDT), which involves collaborative decision-making between human physicians and AI systems. The human-computer MDT approach in pulmonary nodule evaluation presents a novel model for diagnosis and treatment, leveraging the respective strengths of human expertise and AI capabilities. This review provides an overview of the background, medical application, advantages and limitations, future trends, and reporting format of the Human-Computer MDT in pulmonary nodule evaluation.</p><p>Its aim is to explore standardized methods for enhancing early diagnosis in lung cancer. With the rapid advancement of AI and the field of <em>meta</em>-cosmic medicine, human-computer MDT are expected to become more widespread and play an important role in the implementation of the Healthy China 2030 plan, particularly in improving primary medical care in the future.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"6 ","pages":"Pages 172-181"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914123000291/pdfft?md5=c95ba481c5a11821bc755208b7b297bd&pid=1-s2.0-S2588914123000291-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138610643","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":"Expert consensus on the “Digital Human” of metaverse in medicine","authors":"Dawei Yang ,&nbsp;Mengting Sun ,&nbsp;Jian Zhou ,&nbsp;Yeting Lu ,&nbsp;Zhenju Song ,&nbsp;Zhihong Chen ,&nbsp;Dong Yang ,&nbsp;Xueling Wu ,&nbsp;Haiyan Ge ,&nbsp;Yuming Zhang ,&nbsp;Chengshi Gao ,&nbsp;Jianwei Xuan ,&nbsp;Xiaoying Li ,&nbsp;Jun Yin ,&nbsp;Xiaodan Zhu ,&nbsp;Jie Liu ,&nbsp;Hongyi Xin ,&nbsp;Weipeng Jiang ,&nbsp;Ningfang Wang ,&nbsp;Yuan Wang ,&nbsp;Chunxue Bai","doi":"10.1016/j.ceh.2023.11.005","DOIUrl":"https://doi.org/10.1016/j.ceh.2023.11.005","url":null,"abstract":"","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"6 ","pages":"Pages 159-163"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S258891412300031X/pdfft?md5=9693a431c3eb3b65fa16a96a79328d2d&pid=1-s2.0-S258891412300031X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138582103","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":"Feasibility, safety and tolerability of CT-guided percutaneous thermal ablation in COPD with malignant pulmonary nodules","authors":"Min Ao ,&nbsp;Yunjiu Hu ,&nbsp;Mi Zhou ,&nbsp;Junhao Mu ,&nbsp;Weiyi Li ,&nbsp;Jing Liu ,&nbsp;Xiaohui Wang ,&nbsp;Li Yang","doi":"10.1016/j.ceh.2023.12.001","DOIUrl":"10.1016/j.ceh.2023.12.001","url":null,"abstract":"<div><p>For early-stage non-small cell lung cancer, surgical resection was used as the first treatment. However, approximately 20% of patients were not suitable for surgery due to severe comorbidities. We verified the feasibility, safety, and tolerability of percutaneous thermal ablation for patients of chronic obstructive pulmonary disease (COPD) with peripheral high-risk pulmonary nodules in the real world. The patients with peripheral high-risk pulmonary nodules ineligible or unwilling to undergo surgery who were ineligible or unwilling tosurgery underwent CT-guided thermal ablation in our hospital from January 1st, 2019 to May 31th, 2022 were retrospectively collected, and divided into COPD and non COPD group. Incidence, severity, risk factors of complications between in different severity of COPD and non-COPD group were compared. A total of 216 high-risk were enrolled, including 73 in COPD group and 143 in the non-COPD group. The average age, male gender, MMRC score, size of nodules, incidence of confirmed pathological diagnosis, and pneumothorax after thermal ablation were higher in the COPD group than in the non-COPD group. COPD was the only independent risk factor for pneumothorax after ablation. The incidence of pneumothorax increased with the severity of COPD, but no statistical significance. Compared to the baseline, the MMRC score was significantly increased in the COPD group, but there was no significant difference in the discharge time and hospitalization expenses between the COPD patients with or without pneumothorax. CT-guided percutaneous thermal ablation is a safe and feasible therapy for different severities of COPD with high-risk pulmonary nodules, and it is well-tolerated without increasing medical burden.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"6 ","pages":"Pages 164-171"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588914123000321/pdfft?md5=c4ad0a244229464eb3797805fa4eb79c&pid=1-s2.0-S2588914123000321-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138615469","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":"Enhancing Parkinson’s disease identification using ensemble classifier and data augmentation techniques in machine learning","authors":"Mohammed Muzaffar Hussain ,&nbsp;D. Weslin ,&nbsp;S. Kumari ,&nbsp;S. Umamaheswari ,&nbsp;K. Kamalakannan","doi":"10.1016/j.ceh.2023.11.002","DOIUrl":"https://doi.org/10.1016/j.ceh.2023.11.002","url":null,"abstract":"<div><p>Parkinson’s disease (PD) is a devastating neurological syndrome that affects millions of people worldwide. For the successful treatment and control of PD, it is essential to detect it early and diagnose it accurately. Machine learning (ML) algorithms have shown promising results in identifying PD based on various clinical and non-invasive measures. This paper proposes an ensemble classifier-based method to identify PD using ML algorithms. We consider two classes of PD, namely, healthy controls and PD patients. Our approach involves the use of feature selection, feature extraction, and classification techniques to develop a robust and accurate model. We use a dataset that includes clinical measures and necessary features from patients with PD and healthy controls. Our outcomes demonstrate the effectiveness of the proposed method in accurately identifying PD and highlight the importance of ML algorithms in assisting with early detection and diagnosis of PD.</p></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"6 ","pages":"Pages 150-158"},"PeriodicalIF":0.0,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S258891412300028X/pdfft?md5=6f306950333c04441c20227f9535ba22&pid=1-s2.0-S258891412300028X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138413602","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}