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  1. 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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  2. 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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  3. 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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  4. 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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  5. 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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  6. 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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  7. 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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  8. 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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  9. 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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  10. 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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  11. 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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  12. 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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  13. 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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  14. 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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  15. 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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  16. 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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  17. 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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  18. 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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  19. 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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  20. 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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  21. 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

  22. 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

  23. 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

  24. 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

  25. 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

  26. 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

  27. 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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  28. 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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  29. 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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  30. 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

    Published on:

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

  31. 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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  32. 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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  33. 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

  34. 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

  35. 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

  36. 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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  37. 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:

  38. 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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  39. 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

    Published on:

  40. 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

  41. 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

    Published on:

  42. 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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  43. 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

    Published on:

  44. 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

    Published on:

  45. 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

    Published on:

  46. 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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  47. 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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  48. 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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  49. 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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