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  1. An individualized approach using shared decision-making (SDM) and goal setting is a person-centred strategy that may facilitate prioritization of treatment options. SDM has not been adopted extensively in clin...

    Authors: Catherine H. Yu, Calvin Ke, Aleksandra Jovicic, Susan Hall and Sharon E. Straus

    Citation: BMC Medical Informatics and Decision Making 2019 19:186

    Content type: Research article

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  2. The incidence of cardiac implantable electronic device infection (CIEDI) is low and usually belongs to the typical imbalanced dataset. We sought to describe our experience on the management of the imbalanced C...

    Authors: Xiang-Fei Feng, Ling-Chao Yang, Li-Zhuang Tan and Yi-Gang Li

    Citation: BMC Medical Informatics and Decision Making 2019 19:185

    Content type: Research article

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  3. Manual coding of phenotypes in brain radiology reports is time consuming. We developed a natural language processing (NLP) algorithm to enable automatic identification of brain imaging in radiology reports per...

    Authors: Emily Wheater, Grant Mair, Cathie Sudlow, Beatrice Alex, Claire Grover and William Whiteley

    Citation: BMC Medical Informatics and Decision Making 2019 19:184

    Content type: Research article

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  4. Medical data sharing is a big challenge in biomedicine, which often hinders collaborative research. Due to privacy concerns, clinical notes cannot be directly shared. A lot of efforts have been dedicated to de...

    Authors: Md Nazmus Sadat, Md Momin Al Aziz, Noman Mohammed, Serguei Pakhomov, Hongfang Liu and Xiaoqian Jiang

    Citation: BMC Medical Informatics and Decision Making 2019 19:183

    Content type: Software

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  5. Kidney allocation is a multi-criteria and complex decision-making problem, which should also consider ethical issues in addition to the medical aspects. Leading countries in this field use a point scoring syst...

    Authors: Nasrin Taherkhani, Mohammad Mehdi Sepehri, Shadi Shafaghi and Toktam Khatibi

    Citation: BMC Medical Informatics and Decision Making 2019 19:182

    Content type: Research article

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  6. Health research apps often do not focus on usability as a design priority. This is problematic when the population of interest is disproportionately underrepresented as users of mobile apps, especially observe...

    Authors: Y. Quintana, D. Fahy, A. M. Abdelfattah, J. Henao and C. Safran

    Citation: BMC Medical Informatics and Decision Making 2019 19:181

    Content type: Study protocol

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  7. The Grog Survey App is a visual and interactive tablet computer-based survey application. It has been shown to be an accurate and acceptable tool to help Indigenous Australians describe what they drink.

    Authors: KS Kylie Lee, James H. Conigrave, Scott Wilson, Jimmy Perry, Noel Hayman, Catherine Zheng, Mustafa Al Ansari, Michael Doyle, Robin Room, Sarah Callinan, Tanya Chikritzhs, Tim Slade and Katherine M. Conigrave

    Citation: BMC Medical Informatics and Decision Making 2019 19:180

    Content type: Research article

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  8. Aponjon (meaning “near and dear ones”), a mobile phone-based mHealth service, customized voice messages for expectant (6–42 weeks pregnancy) and new mothers (1–52 weeks after delivery) for promotion of recommende...

    Authors: Mahbub Elahi Chowdhury, Shafayatul Islam Shiblee and Heidi E. Jones

    Citation: BMC Medical Informatics and Decision Making 2019 19:179

    Content type: Research article

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  9. The collection of data and biospecimens which characterize patients and probands in-depth is a core element of modern biomedical research. Relevant data must be considered highly sensitive and it needs to be p...

    Authors: Florian Kohlmayer, Ronald Lautenschläger and Fabian Prasser

    Citation: BMC Medical Informatics and Decision Making 2019 19:178

    Content type: Debate

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  10. Following publication of the original manuscript [1], the authors noted several errors in Table 1. Details of the requested corrections are shown below:

    Authors: Marcello Tonelli, Natasha Wiebe, Martin Fortin, Bruce Guthrie, Brenda R. Hemmelgarn, Matthew T. James, Scott W. Klarenbach, Richard Lewanczuk, Braden J. Manns, Paul Ronksley, Peter Sargious, Sharon Straus and Hude Quan

    Citation: BMC Medical Informatics and Decision Making 2019 19:177

    Content type: Correction

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    The original article was published in BMC Medical Informatics and Decision Making 2015 15:31

  11. Even though a high demand for sector spanning communication exists, so far no eHealth platform for nephrology is established within Germany. This leads to insufficient communication between medical providers a...

    Authors: L. Pape, N. Schneider, T. Schleef, U. Junius-Walker, H. Haller, R. Brunkhorst, N. Hellrung, H. U. Prokosch, B. Haarbrandt, M. Marschollek and M. Schiffer

    Citation: BMC Medical Informatics and Decision Making 2019 19:176

    Content type: Study protocol

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  12. This study explores opinions and experiences of people with Parkinson’s disease (PwP) in Sweden of using self-tracking. Parkinson’s disease (PD) is a neurodegenerative condition entailing varied and changing s...

    Authors: Sara Riggare, Therese Scott Duncan, Helena Hvitfeldt and Maria Hägglund

    Citation: BMC Medical Informatics and Decision Making 2019 19:175

    Content type: Research article

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  13. To evaluate the effectiveness of audit and communication strategies to reduce diagnostic errors made by clinicians.

    Authors: Julie Abimanyi-Ochom, Shalika Bohingamu Mudiyanselage, Max Catchpool, Marnie Firipis, Sithara Wanni Arachchige Dona and Jennifer J. Watts

    Citation: BMC Medical Informatics and Decision Making 2019 19:174

    Content type: Research article

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  14. Feelings of depression can be caused by negative life events (NLE) such as the death of a family member, a quarrel with one’s spouse, job loss, or strong criticism from an authority figure. The automatic and a...

    Authors: Jheng-Long Wu, Xiang Xiao, Liang-Chih Yu, Shao-Zhen Ye and K. Robert Lai

    Citation: BMC Medical Informatics and Decision Making 2019 19:173

    Content type: Technical advance

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  15. The admission, discharge and transfer (ADT) module is used in the hospital information system (HIS) for the purposes of managing appointments, patient admission, daily control of hospital beds, planning surger...

    Authors: Razieh Farrahi, Fatemeh Rangraz Jeddi, Ehsan Nabovati, Monireh Sadeqi Jabali and Reza Khajouei

    Citation: BMC Medical Informatics and Decision Making 2019 19:172

    Content type: Research article

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  16. A substantial proportion of microbiological screening in diagnostic laboratories is due to suspected urinary tract infections (UTIs), yet approximately two thirds of urine samples typically yield negative cult...

    Authors: Ross J. Burton, Mahableshwar Albur, Matthias Eberl and Simone M. Cuff

    Citation: BMC Medical Informatics and Decision Making 2019 19:171

    Content type: Research article

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  17. The increasing complexity and volume of clinical data poses a challenge in the decision-making process. Data visualizations can assist in this process by speeding up the time required to analyze and understand...

    Authors: Andres Ledesma, Niranjan Bidargaddi, Jörg Strobel, Geoffrey Schrader, Hannu Nieminen, Ilkka Korhonen and Miikka Ermes

    Citation: BMC Medical Informatics and Decision Making 2019 19:170

    Content type: Research article

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  18. Identifying individuals who are unlikely to adhere to a physical exercise regime has potential to improve physical activity interventions. The aim of this paper is to develop and test adherence prediction mode...

    Authors: Mo Zhou, Yoshimi Fukuoka, Ken Goldberg, Eric Vittinghoff and Anil Aswani

    Citation: BMC Medical Informatics and Decision Making 2019 19:169

    Content type: Research article

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  19. Electronic health records are now widely adopted in medical and behavioral health settings. While they have the potential to improve the quality of care, the research findings on their impact on clinical pract...

    Authors: Victoria Stanhope and Elizabeth B. Matthews

    Citation: BMC Medical Informatics and Decision Making 2019 19:168

    Content type: Research article

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  20. Thrombophilia testing is frequently ordered in the inpatient setting despite its limited impact on clinical decision-making and unreliable results in the setting of acute thrombosis or ongoing anticoagulation....

    Authors: Henry Kwang, Eric Mou, Ilana Richman, Andre Kumar, Caroline Berube, Rajani Kaimal, Neera Ahuja, Stephanie Harman, Tyler Johnson, Neil Shah, Ronald Witteles, Robert Harrington, Lisa Shieh and Jason Hom

    Citation: BMC Medical Informatics and Decision Making 2019 19:167

    Content type: Research article

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  21. The increasing use of common data elements (CDEs) in numerous research projects and clinical applications has made it imperative to create an effective classification scheme for the efficient management of the...

    Authors: Hye Hyeon Kim, Yu Rang Park, Kye Hwa Lee, Young Soo Song and Ju Han Kim

    Citation: BMC Medical Informatics and Decision Making 2019 19:166

    Content type: Technical advance

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  22. Most breast cancer patients undergoing mastectomy are candidates for breast reconstruction. Deciding about breast reconstruction is complex and the preference-sensitive nature of this decision requires an appr...

    Authors: Jacqueline A. ter Stege, Leonie A. E. Woerdeman, Daniela E. E. Hahn, Martine A. van Huizum, Frederieke H. van Duijnhoven, Jacobien M. Kieffer, Valesca P. Retèl, Kerry A. Sherman, Arjen J. Witkamp, Hester S. A. Oldenburg and Eveline M. A. Bleiker

    Citation: BMC Medical Informatics and Decision Making 2019 19:165

    Content type: Study protocol

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  23. Machine learning has been used extensively in clinical text classification tasks. Deep learning approaches using word embeddings have been recently gaining momentum in biomedical applications. In an effort to ...

    Authors: Jihad S. Obeid, Erin R. Weeda, Andrew J. Matuskowitz, Kevin Gagnon, Tami Crawford, Christine M. Carr and Lewis J. Frey

    Citation: BMC Medical Informatics and Decision Making 2019 19:164

    Content type: Research article

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  24. To understand user needs, system requirements and organizational conditions towards successful design and adoption of Clinical Decision Support Systems for Type 2 Diabetes (T2D) care built on top of computeriz...

    Authors: Giuseppe Fico, Liss Hernanzez, Jorge Cancela, Arianna Dagliati, Lucia Sacchi, Antonio Martinez-Millana, Jorge Posada, Lidia Manero, Jose Verdú, Andrea Facchinetti, Manuel Ottaviano, Konstantia Zarkogianni, Konstantina Nikita, Leif Groop, Rafael Gabriel-Sanchez, Luca Chiovato…

    Citation: BMC Medical Informatics and Decision Making 2019 19:163

    Content type: Research article

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  25. There is growing interest in sensor-based assessment of upper limb tremor in multiple sclerosis and other movement disorders. However, previously such assessments have not been found to offer any improvement o...

    Authors: David G. Western, Simon A. Neild, Rosemary Jones and Angela Davies-Smith

    Citation: BMC Medical Informatics and Decision Making 2019 19:162

    Content type: Research article

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  26. Healthcare professionals’ adherence to guidelines on child protection is not self-evident. This study assessed the effects of a computerised support tool on child healthcare professionals’ adherence to the sev...

    Authors: Annemieke A. J. Konijnendijk, Magda M. Boere-Boonekamp, Maria E. Haasnoot and Ariana Need

    Citation: BMC Medical Informatics and Decision Making 2019 19:161

    Content type: Research article

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  27. Electronic health records (EHRs) are an elementary part of the work of registered nurses (RNs) in healthcare. RNs are the largest group of healthcare workers, and their experiences with EHRs and their informat...

    Authors: Tuulikki Vehko, Hannele Hyppönen, Sampsa Puttonen, Sari Kujala, Eeva Ketola, Johanna Tuukkanen, Anna-Mari Aalto and Tarja Heponiemi

    Citation: BMC Medical Informatics and Decision Making 2019 19:160

    Content type: Research article

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  28. Drug-drug interactions (DDIs) can cause patient harm. Between 46 and 90% of patients admitted to the Intensive Care Unit (ICU) are exposed to potential DDIs (pDDIs). This rate is twice as high as patients on g...

    Authors: T. Bakker, J. E. Klopotowska, S. Eslami, D. W. de Lange, R. van Marum, H. van der Sijs, E. de Jonge, D. A. Dongelmans, N. F. de Keizer and A. Abu-Hanna

    Citation: BMC Medical Informatics and Decision Making 2019 19:159

    Content type: Study protocol

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  29. 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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  30. 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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  31. 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

  32. 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

    Published on:

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

  33. 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

  34. 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

    Published on:

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

  35. 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

  36. 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

  37. 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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  38. 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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  39. 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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  40. 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

  41. 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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  42. 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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  43. 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

    Published on:

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

  44. 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

    Published on:

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

  45. 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

  46. 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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  47. 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

    Published on:

  48. 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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  49. 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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