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  1. 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

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

  2. 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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  3. 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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  4. 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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  5. 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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  6. 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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  7. 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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  8. 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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  9. 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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  10. 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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  11. 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

  12. 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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  13. 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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  14. 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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  15. 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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  16. 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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  17. 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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  18. 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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  19. 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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  20. 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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  21. 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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  22. 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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  23. 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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  24. 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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  25. 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

  26. 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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  27. 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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  28. 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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  29. Cardiovascular risk management (CVRM) is notoriously difficult because of multi-morbidity and the different phenotypes and severities of cardiovascular disease. Computerized decision support systems (CDSS) ena...

    Authors: T. Katrien J. Groenhof, Folkert W. Asselbergs, Rolf H. H. Groenwold, Diederick E. Grobbee, Frank L. J. Visseren and Michiel L. Bots

    Citation: BMC Medical Informatics and Decision Making 2019 19:108

    Content type: Research article

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  30. Evidence-Based Medicine (EBM) is the process of systematically locating, searching, evaluating, and using contemporaneous research findings as the basis for clinical decision making. The systematic review show...

    Authors: Teshager Worku, Meron Yeshitila, Tilaye Feto, Shiferaw Leta, Frehiwot Mesfin and Haymanot Mezmur

    Citation: BMC Medical Informatics and Decision Making 2019 19:107

    Content type: Research article

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  31. Pain is the most common and distressing symptom for patients in all clinical settings. The dearth of health informatics tools to support acute and chronic pain management may be contributing to the chronic pai...

    Authors: Peng Zhao, Illhoi Yoo, Robert Lancey and Ebby Varghese

    Citation: BMC Medical Informatics and Decision Making 2019 19:106

    Content type: Research article

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  32. Home monitoring of urine protein is a critical component of disease management in childhood nephrotic syndrome. We describe the development of a novel mobile application, UrApp – Nephrotic Syndrome Manager, to...

    Authors: Chia-shi Wang, Richard Boyd, Russell Mitchell, W. Darryl Wright, Courtney McCracken, Cam Escoffery, Rachel E. Patzer and Larry A. Greenbaum

    Citation: BMC Medical Informatics and Decision Making 2019 19:105

    Content type: Technical advance

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  33. Although previous research showed that telehealth services can reduce the misuse of resources and urban–rural disparities, most healthcare insurers do not include telehealth services in their health insurance ...

    Authors: Ching-Chin Chern, Yu-Jen Chen and Bo Hsiao

    Citation: BMC Medical Informatics and Decision Making 2019 19:104

    Content type: Research article

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  34. Disease trajectories for chronic diseases can span over several decades, with several time-dependent factors affecting treatment decisions. Thus, there is a need for long-term predictions of disease trajectori...

    Authors: Eugenio Ventimiglia, Mieke Van Hemelrijck, Lars Lindhagen, Pär Stattin and Hans Garmo

    Citation: BMC Medical Informatics and Decision Making 2019 19:103

    Content type: Research article

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  35. Inappropriate prescribing of psychotropics is a persistent and prevalent problem in nursing homes. The present study compared inappropriate prescribing of psychotropics in nursing homes 16 years apart with pre...

    Authors: Jan Schjøtt and Jörg Aßmus

    Citation: BMC Medical Informatics and Decision Making 2019 19:102

    Content type: Research article

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  36. Vaccination has been one of the most successful public health interventions to date, and the U.S. FDA/CDC Vaccine Adverse Event Reporting System (VAERS) currently contains more than 500,000 reports for post-vacci...

    Authors: Jian-Jian Ren, Tingni Sun, Yongqun He and Yuji Zhang

    Citation: BMC Medical Informatics and Decision Making 2019 19:101

    Content type: Research article

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  37. The 2014–2016 West Africa Ebola epidemic highlighted the difficulty of collecting patient information during emergencies, especially in highly infectious environments. Health information systems (HISs) appropr...

    Authors: Shefali Oza, Kevin Wing, Alieu Amara Sesay, Sabah Boufkhed, Catherine Houlihan, Lahai Vandi, Sahr Charles Sebba, Catherine R. McGowan, Rachael Cummings and Francesco Checchi

    Citation: BMC Medical Informatics and Decision Making 2019 19:100

    Content type: Research article

    Published on:

  38. Numerous patients suffer from chronic wounds and wound infections nowadays. Until now, the care for wounds after surgery still remain a tedious and challenging work for the medical personnel and patients. As ...

    Authors: Jui-Tse Hsu, Yung-Wei Chen, Te-Wei Ho, Hao-Chih Tai, Jin-Ming Wu, Hsin-Yun Sun, Chi-Sheng Hung, Yi-Chong Zeng, Sy-Yen Kuo and Feipei Lai

    Citation: BMC Medical Informatics and Decision Making 2019 19:99

    Content type: Research article

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  39. Multiple predictive scores using Electronic Patient Record data have been developed for hospitalised patients at risk of clinical deterioration. Methods used to select patient centred variables for inclusion i...

    Authors: James Malycha, Timothy Bonnici, David A. Clifton, Guy Ludbrook, J. Duncan Young and Peter J. Watkinson

    Citation: BMC Medical Informatics and Decision Making 2019 19:98

    Content type: Research article

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  40. Mobile health (MH) technologies including clinical decision support systems (CDSS) provide an efficient method for patient monitoring and treatment. A mobile CDSS is based on real-time sensor data and historic...

    Authors: Shaker El-Sappagh, Farman Ali, Abdeltawab Hendawi, Jun-Hyeog Jang and Kyung-Sup Kwak

    Citation: BMC Medical Informatics and Decision Making 2019 19:97

    Content type: Research article

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  41. Assessing risks of bias in randomized controlled trials (RCTs) is an important but laborious task when conducting systematic reviews. RobotReviewer (RR), an open-source machine learning (ML) system, semi-autom...

    Authors: Frank Soboczenski, Thomas A. Trikalinos, Joël Kuiper, Randolph G. Bias, Byron C. Wallace and Iain J. Marshall

    Citation: BMC Medical Informatics and Decision Making 2019 19:96

    Content type: Research article

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  42. Patients and citizens need access to their health information to get a retrospective as well as a prospective view on their care and rehabilitation processes. However, patients’ health information is stored in...

    Authors: Nadia Davoody, Sabine Koch, Ingvar Krakau and Maria Hägglund

    Citation: BMC Medical Informatics and Decision Making 2019 19:95

    Content type: Research article

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  43. Although fecal hemoglobin concentration (f-Hb) was highly associated with the risk of colorectal neoplasms, current studies on this subject are hampered by skewedness of the data and the ordinal property of f-...

    Authors: Szu-Min Peng, Han-Mo Chiu, Hsiao-Hsuan Jen, Chen-Yang Hsu, Sam Li-Sheng Chen, Sherry Yueh-Hsia Chiu, Amy Ming-Fang Yen, Jean Ching-Yuan Fann, Yi-Chia Lee and Hsiu-Hsi Chen

    Citation: BMC Medical Informatics and Decision Making 2019 19:94

    Content type: Research article

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  44. While early diagnostic decision support systems were built around knowledge bases, more recent systems employ machine learning to consume large amounts of health data. We argue curated knowledge bases will rem...

    Authors: Lars Müller, Rashmi Gangadharaiah, Simone C. Klein, James Perry, Greg Bernstein, David Nurkse, Dustin Wailes, Rishi Graham, Robert El-Kareh, Sanjay Mehta, Staal A. Vinterbo and Eliah Aronoff-Spencer

    Citation: BMC Medical Informatics and Decision Making 2019 19:93

    Content type: Database

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  45. Maintaining physical fitness is a crucial component of the therapeutic process for patients with cardiovascular disease (CVD). Despite the known importance of being physically active, patient adherence to exer...

    Authors: Kristina Livitckaia, Vassilis Koutkias, Evangelia Kouidi, Mark van Gils, Nikolaos Maglaveras and Ioanna Chouvarda

    Citation: BMC Medical Informatics and Decision Making 2019 19:92

    Content type: Research article

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  46. Many clinical concepts are standardized under a categorical and hierarchical taxonomy such as ICD-10, ATC, etc. These taxonomic clinical concepts provide insight into semantic meaning and similarity among clin...

    Authors: Zheng Jia, Xudong Lu, Huilong Duan and Haomin Li

    Citation: BMC Medical Informatics and Decision Making 2019 19:91

    Content type: Research article

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  47. Data-intensive research in medicine and healthcare such as health-related big data research (HBDR) implies that data from clinical routine, research and patient-reported data, but also non-medical social or de...

    Authors: Katharina Beier, Mark Schweda and Silke Schicktanz

    Citation: BMC Medical Informatics and Decision Making 2019 19:90

    Content type: Debate

    Published on:

  48. Following publication of the original article [1], the authors reported an error in one of the authors’ names.

    Authors: Vivienne J. Zhu, Leslie A. Lenert, Brian E. Bunnell, Jihad S. Obeid, Melanie Jefferson and Chanita Hughes Halbert

    Citation: BMC Medical Informatics and Decision Making 2019 19:89

    Content type: Correction

    Published on:

    The original article was published in BMC Medical Informatics and Decision Making 2019 19:43

  50. The gateway hypothesis (and particularly the prediction of developmental stages in drug abuse) has been a subject of protracted debate since the 1970s. Extensive research has gone into this subject, but has yi...

    Authors: Phillip C. S. R. Kilgore, Nadejda Korneeva, Thomas C. Arnold, Marjan Trutschl and Urška Cvek

    Citation: BMC Medical Informatics and Decision Making 2019 19:87

    Content type: Software

    Published on:

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