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  1. Collective intelligence, facilitated by information technology or manual techniques, refers to the collective insight of groups working on a task and has the potential to generate more accurate information or ...

    Authors: Kate Radcliffe, Helena C. Lyson, Jill Barr-Walker and Urmimala Sarkar

    Citation: BMC Medical Informatics and Decision Making 2019 19:158

    Content type: Research article

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  2. Patients generate large amounts of digital data through devices, social media applications, and other online activities. Little is known about patients’ perception of the data they generate online and its rela...

    Authors: Emily Seltzer, Jesse Goldshear, Sharath Chandra Guntuku, Dave Grande, David A. Asch, Elissa V. Klinger and Raina M. Merchant

    Citation: BMC Medical Informatics and Decision Making 2019 19:157

    Content type: Research article

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  3. The existing community-wide bodies of biomedical ontologies are known to contain quality and content problems. Past research has revealed various errors related to their semantics and logical structure. Automa...

    Authors: Muhammad Amith, Frank Manion, Chen Liang, Marcelline Harris, Dennis Wang, Yongqun He and Cui Tao

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 4):152

    Content type: Research

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    This article is part of a Supplement: Volume 19 Supplement 4

  4. Padua linear model is widely used for the risk assessment of venous thromboembolism (VTE), a common but preventable complication for inpatients. However, genetic and environmental differences between Western a...

    Authors: Yuqing Yang, Xin Wang, Yu Huang, Ning Chen, Juhong Shi and Ting Chen

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 4):151

    Content type: Research

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    This article is part of a Supplement: Volume 19 Supplement 4

  5. Dietary supplements (DSs) are widely used. However, consumers know little about the safety and efficacy of DSs. There is a growing interest in accessing health information online; however, health information, ...

    Authors: Xing He, Rui Zhang, Rubina Rizvi, Jake Vasilakes, Xi Yang, Yi Guo, Zhe He, Mattia Prosperi, Jinhai Huo, Jordan Alpert and Jiang Bian

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 4):150

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 19 Supplement 4

  6. The aging population has led to an increase in cognitive impairment (CI) resulting in significant costs to patients, their families, and society. A research endeavor on a large cohort to better understand the ...

    Authors: Somaieh Goudarzvand, Jennifer St. Sauver, Michelle M. Mielke, Paul Y. Takahashi, Yugyung Lee and Sunghwan Sohn

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 4):149

    Content type: Research

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    This article is part of a Supplement: Volume 19 Supplement 4

  7. In this editorial, we first summarize the Third International Workshop on Semantics-Powered Data Analytics (SEPDA 2018) held on December 3, 2018 in conjunction with the 2018 IEEE International Conference on Bi...

    Authors: Zhe He, Jiang Bian, Cui Tao and Rui Zhang

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 4):148

    Content type: Introduction

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    This article is part of a Supplement: Volume 19 Supplement 4

  8. Hepatitis C affects about 3 % of the world’s population. In the United States, about 3.5 million have chronic hepatitis C, and it is the leading cause of liver cancer and the most common indication for liver t...

    Authors: Jing Huang, Xinyuan Zhang, Jiayi Tong, Jingcheng Du, Rui Duan, Liu Yang, Jason H. Moore, Cui Tao and Yong Chen

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 4):147

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 19 Supplement 4

  9. Imaging examinations, such as ultrasonography, magnetic resonance imaging and computed tomography scans, play key roles in healthcare settings. To assess and improve the quality of imaging diagnosis, we need t...

    Authors: Tao Zheng, Yimei Gao, Fei Wang, Chenhao Fan, Xingzhi Fu, Mei Li, Ya Zhang, Shaodian Zhang and Handong Ma

    Citation: BMC Medical Informatics and Decision Making 2019 19:156

    Content type: Research article

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  10. The potential for smartphones to revolutionize the way that medical doctors practice has become a reality, particularly in specialities where visual examination is a principal step in assessing a medical case,...

    Authors: Ali Jasem Buabbas, Prem Sharma, Adel Al-Abdulrazaq and Hashem Shehab

    Citation: BMC Medical Informatics and Decision Making 2019 19:155

    Content type: Research article

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  11. Female BRCA1 and BRCA2 mutation carriers have an increased lifetime risk of developing breast and/or ovarian cancer. Hence, they face the difficult decision of choosing a preventive strategy such as risk-reducing...

    Authors: Lisa Krassuski, Vera Vennedey, Stephanie Stock and Sibylle Kautz-Freimuth

    Citation: BMC Medical Informatics and Decision Making 2019 19:154

    Content type: Research article

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  12. Following publication of the original article

    Authors: Muhammad Naseer Bajwa, Muhammad Imran Malik, Shoaib Ahmed Siddiqui, Andreas Dengel, Faisal Shafait, Wolfgang Neumeier and Sheraz Ahmed

    Citation: BMC Medical Informatics and Decision Making 2019 19:153

    Content type: Correction

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    The original article was published in BMC Medical Informatics and Decision Making 2019 19:136

  13. Although complex machine learning models are commonly outperforming the traditional simple interpretable models, clinicians find it hard to understand and trust these complex models due to the lack of intuitio...

    Authors: Radwa Elshawi, Mouaz H. Al-Mallah and Sherif Sakr

    Citation: BMC Medical Informatics and Decision Making 2019 19:146

    Content type: Research article

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  14. A user-centered design approach for eHealth interventions improves their effectiveness in stroke rehabilitation. Nevertheless, insight into requirements of end-users (patients/informal caregivers and/or health...

    Authors: Manon Wentink, L. van Bodegom-Vos, B. Brouns, H. Arwert, S. Houdijk, P. Kewalbansing, L. Boyce, T. Vliet Vlieland, A. de Kloet and J. Meesters

    Citation: BMC Medical Informatics and Decision Making 2019 19:145

    Content type: Research article

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  15. After publication of this supplement article [1], it was brought to our attention that the first and correspondence authors’ affiliation information was incorrectly spelt. The original spelling was written as ...

    Authors: Xia Zhao, Xiaohua Li, Wei Yang, Qianjin Feng, Yi Zhou and Qiong Wang

    Citation: BMC Medical Informatics and Decision Making 2019 19:144

    Content type: Correction

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    The original article was published in BMC Medical Informatics and Decision Making 2018 18:112

  16. Approximately 20% of deaths in the US each year are attributable to smoking, yet current practices in the recording of this health risk in electronic health records (EHRs) have not led to discernable changes i...

    Authors: Ellen L. Palmer, John Higgins, Saeed Hassanpour, James Sargent, Christina M. Robinson, Jennifer A. Doherty and Tracy Onega

    Citation: BMC Medical Informatics and Decision Making 2019 19:143

    Content type: Research article

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    The Research article to this article has been published in BMC Medical Informatics and Decision Making 2019 19:141

  17. Usage of structured fields in Electronic Health Records (EHRs) to ascertain smoking history is important but fails in capturing the nuances of smoking behaviors. Knowledge of smoking behaviors, such as pack ye...

    Authors: Ellen L. Palmer, Saeed Hassanpour, John Higgins, Jennifer A. Doherty and Tracy Onega

    Citation: BMC Medical Informatics and Decision Making 2019 19:141

    Content type: Research article

    Published on:

    The Research article to this article has been published in BMC Medical Informatics and Decision Making 2019 19:143

  18. Identifying implausible clinical observations (e.g., laboratory test and vital sign values) in Electronic Health Record (EHR) data using rule-based procedures is challenging. Anomaly/outlier detection methods ...

    Authors: Hossein Estiri, Jeffrey G. Klann and Shawn N. Murphy

    Citation: BMC Medical Informatics and Decision Making 2019 19:142

    Content type: Technical advance

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  19. The challenges faced by caregivers of the elderly with chronic diseases are always complex. In this context, mobile technologies have been used with promising results, but often have restricted functionality, ...

    Authors: Matheus Costa Stutzel, Michel Pedro Filippo, Alexandre Sztajnberg, Rosa Maria E.M. da Costa, André da Silva Brites, Luciana Branco da Motta and Célia Pereira Caldas

    Citation: BMC Medical Informatics and Decision Making 2019 19:140

    Content type: Research article

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  20. Despite WHO guidelines for testing all suspected cases of malaria before initiating treatment, presumptive malaria treatment remains common practice among some clinicians and in certain low-resource settings t...

    Authors: S. Smith, R. Koech, D. Nzorubara, M. Otieno, L. Wong, G. Bhat, E. van den Bogaart, M. Thuranira, D. Onchonga and T. F. Rinke de Wit

    Citation: BMC Medical Informatics and Decision Making 2019 19:139

    Content type: Technical advance

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  21. Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably duri...

    Authors: Brian W. Patterson, Gwen C. Jacobsohn, Manish N. Shah, Yiqiang Song, Apoorva Maru, Arjun K. Venkatesh, Monica Zhong, Katherine Taylor, Azita G. Hamedani and Eneida A. Mendonça

    Citation: BMC Medical Informatics and Decision Making 2019 19:138

    Content type: Research article

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  22. With the advancement of powerful image processing and machine learning techniques, Computer Aided Diagnosis has become ever more prevalent in all fields of medicine including ophthalmology. These methods conti...

    Authors: Muhammad Naseer Bajwa, Muhammad Imran Malik, Shoaib Ahmed Siddiqui, Andreas Dengel, Faisal Shafait, Wolfgang Neumeier and Sheraz Ahmed

    Citation: BMC Medical Informatics and Decision Making 2019 19:136

    Content type: Research article

    Published on:

    The Correction to this article has been published in BMC Medical Informatics and Decision Making 2019 19:153

  23. Medication therapy management (MTM) is a service, most commonly provided by pharmacists, intended to identify and resolve medication therapy problems (MTPs) to enhance patient care. MTM is typically documented...

    Authors: Margie E. Snyder, Heather Jaynes, Stephanie A. Gernant, Julie DiIulio, Laura G. Militello, William R. Doucette, Omolola A. Adeoye and Alissa L. Russ

    Citation: BMC Medical Informatics and Decision Making 2019 19:135

    Content type: Research article

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  24. A large provider of community health services (an NHS Trust in England) deployed Apple iPads to its front-line community-based healthcare clinicians (predominantly nurses) to enable them to increase responsive...

    Authors: Jasmine Harvey and John Powell

    Citation: BMC Medical Informatics and Decision Making 2019 19:134

    Content type: Research article

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  25. A 2016 study standardized the definition of stillbirths. It estimated the rate as a proportion of total births. A 2015 paper addressed the problem of disability-adjusted life-years (DALY) for stillbirths. Ther...

    Authors: Chander Kant

    Citation: BMC Medical Informatics and Decision Making 2019 19:133

    Content type: Debate

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  26. This paper presents a conditional random fields (CRF) method that enables the capture of specific high-order label transition factors to improve clinical named entity recognition performance. Consecutive clini...

    Authors: Wangjin Lee and Jinwook Choi

    Citation: BMC Medical Informatics and Decision Making 2019 19:132

    Content type: Technical advance

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  27. High utilizers receive great attention in health care research because they have a largely disproportionate spending. Existing analyses usually identify high utilizers with an empirical threshold on the number...

    Authors: Chengliang Yang, Chris Delcher, Elizabeth Shenkman and Sanjay Ranka

    Citation: BMC Medical Informatics and Decision Making 2019 19:131

    Content type: Research article

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  28. Patient decision aids (PDAs) can support the treatment decision making process and empower patients to take a proactive role in their treatment pathway while using a shared decision-making (SDM) approach makin...

    Authors: Anshu Ankolekar, Ben G. L. Vanneste, Esther Bloemen-van Gurp, Joep G. van Roermund, Evert J. van Limbergen, Kees van de Beek, Tom Marcelissen, Victor Zambon, Matthias Oelke, Andre Dekker, Cheryl Roumen, Philippe Lambin, Adriana Berlanga and Rianne Fijten

    Citation: BMC Medical Informatics and Decision Making 2019 19:130

    Content type: Technical advance

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  29. Electronic patient portals are increasingly being implemented, also in (haemato) oncology. However, portal usage is low and depends on user and provider engagement. We explored wishes, expectations and thought...

    Authors: Paul A. F. Geerts, Trudy van der Weijden, Pien G. M. Loeffen, Lise E. F. Janssen, Celine Almekinders, Tobias A. Wienhold and Gerard M. J. Bos

    Citation: BMC Medical Informatics and Decision Making 2019 19:129

    Content type: Research article

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  30. Dementia is underdiagnosed in both the general population and among Veterans. This underdiagnosis decreases quality of life, reduces opportunities for interventions, and increases health-care costs. New approa...

    Authors: Yijun Shao, Qing T. Zeng, Kathryn K. Chen, Andrew Shutes-David, Stephen M. Thielke and Debby W. Tsuang

    Citation: BMC Medical Informatics and Decision Making 2019 19:128

    Content type: Research article

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  31. A verbal autopsy (VA) is a post-hoc written interview report of the symptoms preceding a person’s death in cases where no official cause of death (CoD) was determined by a physician. Current leading automated ...

    Authors: Serena Jeblee, Mireille Gomes, Prabhat Jha, Frank Rudzicz and Graeme Hirst

    Citation: BMC Medical Informatics and Decision Making 2019 19:127

    Content type: Research article

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  32. Following publication of the original article [1], the authors reported an error in one of the authors’ names. In this Correction the incorrect and correct author name are shown. The original publication of th...

    Authors: Joseph K. Nuamah, Farzan Sasangohar, Madhav Erraguntla and Ranjana K. Mehta

    Citation: BMC Medical Informatics and Decision Making 2019 19:126

    Content type: Correction

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    The original article was published in BMC Medical Informatics and Decision Making 2019 19:113

  33. Coordination of care, especially after a patient experiences an acute care event, is a challenge for many health systems. Event notification is a form of health information exchange (HIE) which has the potenti...

    Authors: Brian E. Dixon, Ashley L. Schwartzkopf, Vivian M. Guerrero, Justine May, Nicholas S. Koufacos, Andrew M. Bean, Joan D. Penrod, Cathy C. Schubert and Kenneth S. Boockvar

    Citation: BMC Medical Informatics and Decision Making 2019 19:125

    Content type: Study protocol

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  34. Decisional conflict is associated with decision quality and may affect decision outcomes. In the health sciences literature, the Decisional Conflict Scale is widely used to measure decisional conflict, yet lim...

    Authors: Rachel A. Pozzar, Donna L. Berry and Fangxin Hong

    Citation: BMC Medical Informatics and Decision Making 2019 19:124

    Content type: Research article

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  35. The autoverification system for coagulation consists of a series of rules that allow normal data to be released without manual verification. With new advances in medical informatics, the laboratory information...

    Authors: Zhongqing Wang, Cheng Peng, Hui Kang, Xia Fan, Runqing Mu, Liping Zhou, Miao He and Bo Qu

    Citation: BMC Medical Informatics and Decision Making 2019 19:123

    Content type: Research article

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  36. According to WHO stroke is a growing societal challenge and the third leading cause of global disease-burden estimated using disability-adjusted life years. Rehabilitation after stroke is an area of mutual int...

    Authors: Uno Fors, Julius T. Kamwesiga, Gunilla M. Eriksson, Lena von Koch and Susanne Guidetti

    Citation: BMC Medical Informatics and Decision Making 2019 19:122

    Content type: Research article

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  37. Many healthcare databases have been routinely collected over the past decades, to support clinical practice and administrative services. However, their secondary use for research is often hindered by restricte...

    Authors: João Rafael Almeida, Rosa Gini, Giuseppe Roberto, Peter Rijnbeek and José Luís Oliveira

    Citation: BMC Medical Informatics and Decision Making 2019 19:121

    Content type: Software

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  38. Administrative health records (AHRs) and electronic medical records (EMRs) are two key sources of population-based data for disease surveillance, but misclassification errors in the data can bias disease estim...

    Authors: Saeed Al-Azazi, Alexander Singer, Rasheda Rabbani and Lisa M. Lix

    Citation: BMC Medical Informatics and Decision Making 2019 19:120

    Content type: Research article

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  39. The provision of medical services by Medical Teams (MT) on Online Healthcare Communities (OHCs) is a novel method employed by geographically-dispersed healthcare professionals to serve one patient simultaneous...

    Authors: Jiaying Li, Hong Wu, Zhaohua Deng, Naiji Lu, Richard Evans and Chenxi Xia

    Citation: BMC Medical Informatics and Decision Making 2019 19:119

    Content type: Research article

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  40. Most of readmission prediction models are implemented at the time of patient discharge. However, interventions which include an early in-hospital component are critical in reducing readmissions and improving p...

    Authors: Natalie Flaks-Manov, Maxim Topaz, Moshe Hoshen, Ran D. Balicer and Efrat Shadmi

    Citation: BMC Medical Informatics and Decision Making 2019 19:118

    Content type: Research article

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  41. Most healthcare data sources store information within their own unique schemas, making reliable and reproducible research challenging. Consequently, researchers have adopted various data models to improve the ...

    Authors: Mark D. Danese, Marc Halperin, Jennifer Duryea and Ryan Duryea

    Citation: BMC Medical Informatics and Decision Making 2019 19:117

    Content type: Technical advance

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  42. Poor adherence compromises medication treatment effectiveness which results in suboptimal illness control. This can lead to increased use of healthcare services, reduction in patients’ quality of life and incr...

    Authors: Bereket Senay, Kassahun Dessie Gashu, Adamu Takele Jemere and Zeleke Abebaw Mekonnen

    Citation: BMC Medical Informatics and Decision Making 2019 19:109

    Content type: Research article

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  43. In low-income settings, community health workers (CHWs) are frequently the first point of contact for newborns. Mobile technology may aid health workers in classifying illness and providing referral and manage...

    Authors: Lauren E. Schaeffer, Salahuddin Ahmed, Mahmoodur Rahman, Rachel Whelan, Sayedur Rahman, Arunangshu Dutta Roy, Tanzia Ahmed Nijhum, Nazmun Nahar Bably, Helen D’Couto, Carly Hudelson, Iffat Ara Jaben, Sayed Rubayet, Abdullah Baqui and Anne CC Lee

    Citation: BMC Medical Informatics and Decision Making 2019 19:116

    Content type: Research article

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  44. Multiple studies have documented bias in medical decision making, but no studies have examined whether this bias extends to medical coding practices. Medical coding is foundational to the US health care enterp...

    Authors: Jacqueline M. Torres, Danielle Hessler-Jones, Carol Yarbrough, Adam Tapley, Raemarie Jimenez and Laura M. Gottlieb

    Citation: BMC Medical Informatics and Decision Making 2019 19:115

    Content type: Research article

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  45. In many low and middle-income countries (LMICs), difficulties in patient identification are a major obstacle to the delivery of longitudinal care. In absence of unique identifiers, biometrics have emerged as a...

    Authors: Lauren P. Etter, Elizabeth J. Ragan, Rachael Campion, David Martinez and Christopher J. Gill

    Citation: BMC Medical Informatics and Decision Making 2019 19:114

    Content type: Technical advance

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  46. A common challenge with all opioid use disorder treatment paths is withdrawal management. When withdrawal symptoms are not effectively monitored and managed, they lead to relapse which often leads to deadly ov...

    Authors: Joseph K. Nuamah, Farzan Sasangohar, Madhav Erraguntla and Ranjana K. Mehta

    Citation: BMC Medical Informatics and Decision Making 2019 19:113

    Content type: Research article

    Published on:

    The Correction to this article has been published in BMC Medical Informatics and Decision Making 2019 19:126

  47. Data mining tools have been increasingly used in health research, with the promise of accelerating discoveries. Lift is a standard association metric in the data mining community. However, health researchers s...

    Authors: Khanh Vu, Rebecca A. Clark, Colin Bellinger, Graham Erickson, Alvaro Osornio-Vargas, Osmar R. Zaïane and Yan Yuan

    Citation: BMC Medical Informatics and Decision Making 2019 19:112

    Content type: Research article

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  48. Dengue is a serious problem around the globe, with 3.9 billion people at risk of the disease. Sri Lanka has recently seen unprecedented rates of dengue with 4.3 times more cases than during the same period ove...

    Authors: May O. Lwin, Anita Sheldenkar, Chitra Panchapakesan, Janelle Shaina Ng, Jerrald Lau, Karthikayen Jayasundar, Kasun Horathalge, Vajira Sampath Rathnayake, Adam W. Crawley and Prasad Wimalaratne

    Citation: BMC Medical Informatics and Decision Making 2019 19:111

    Content type: Software

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  49. Health and social care interventions show promise as a way of managing the progression of frailty in older adults. Information technology could improve the availability of interventions and services for older ...

    Authors: Holly Gwyther, Lex van Velsen, Rachel L. Shaw, Barbara D’Avanzo, Maria Bujnowska-Fedak, Donata Kurpas, Katarzyna Szwamel, Jan-Willem van’t Klooster and Carol Holland

    Citation: BMC Medical Informatics and Decision Making 2019 19:110

    Content type: Research article

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