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  1. Machine learning is a branch of Artificial Intelligence that is concerned with the design and development of algorithms, and it enables today’s computers to have the property of learning. Machine learning is g...

    Authors: Mohamed Alloghani, Ahmed Aljaaf, Abir Hussain, Thar Baker, Jamila Mustafina, Dhiya Al-Jumeily and Mohammed Khalaf
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 9):253

    This article is part of a Supplement: Volume 19 Supplement 9

    The Correction to this article has been published in BMC Medical Informatics and Decision Making 2020 20:93

  2. Assessment and rating of Parkinson’s Disease (PD) are commonly based on the medical observation of several clinical manifestations, including the analysis of motor activities. In particular, medical specialist...

    Authors: Domenico Buongiorno, Ilaria Bortone, Giacomo Donato Cascarano, Gianpaolo Francesco Trotta, Antonio Brunetti and Vitoantonio Bevilacqua
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 9):243

    This article is part of a Supplement: Volume 19 Supplement 9

  3. With the character of high incidence, high prevalence and high mortality, stroke has brought a heavy burden to families and society in China. In 2009, the Ministry of Health of China launched the China nationa...

    Authors: Xuemeng Li, Di Bian, Jinghui Yu, Mei Li and Dongsheng Zhao
    Citation: BMC Medical Informatics and Decision Making 2019 19:261
  4. Machine learning can assist with multiple tasks during systematic reviews to facilitate the rapid retrieval of relevant references during screening and to identify and extract information relevant to the study...

    Authors: Austin J. Brockmeier, Meizhi Ju, Piotr Przybyła and Sophia Ananiadou
    Citation: BMC Medical Informatics and Decision Making 2019 19:256
  5. Extracting useful information from biomedical literature plays an important role in the development of modern medicine. In natural language processing, there have been rigorous attempts to find meaningful rela...

    Authors: Go Eun Heo, Qing Xie, Min Song and Jeong-Hoon Lee
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):240

    This article is part of a Supplement: Volume 19 Supplement 5

  6. Lung cancer is the second most common cancer for men and women; the wide adoption of electronic health records (EHRs) offers a potential to accelerate cohort-related epidemiological studies using informatics a...

    Authors: Liwei Wang, Lei Luo, Yanshan Wang, Jason Wampfler, Ping Yang and Hongfang Liu
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):239

    This article is part of a Supplement: Volume 19 Supplement 5

  7. Accurately recognizing rare diseases based on symptom description is an important task in patient triage, early risk stratification, and target therapies. However, due to the very nature of rare diseases, the ...

    Authors: Xuedong Li, Yue Wang, Dongwu Wang, Walter Yuan, Dezhong Peng and Qiaozhu Mei
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):238

    This article is part of a Supplement: Volume 19 Supplement 5

  8. With the wide application of Electronic Medical Record (EMR) systems, it has become a daily work for doctors using keyboards to input clinical information into the EMR system. Chinese Input Method Engine (IME)...

    Authors: Feihong Yang, Haihong Guo and Jiao Li
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):237

    This article is part of a Supplement: Volume 19 Supplement 5

  9. To detect attributes of medical concepts in clinical text, a traditional method often consists of two steps: named entity recognition of attributes and then relation classification between medical concepts and...

    Authors: Jun Xu, Zhiheng Li, Qiang Wei, Yonghui Wu, Yang Xiang, Hee-Jin Lee, Yaoyun Zhang, Stephen Wu and Hua Xu
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):236

    This article is part of a Supplement: Volume 19 Supplement 5

  10. Clinical named entity recognition (CNER) is important for medical information mining and establishment of high-quality knowledge map. Due to the different text features from natural language and a large number...

    Authors: Luqi Li, Jie Zhao, Li Hou, Yunkai Zhai, Jinming Shi and Fangfang Cui
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):235

    This article is part of a Supplement: Volume 19 Supplement 5

  11. To robustly identify synergistic combinations of drugs, high-throughput screenings are desirable. It will be of great help to automatically identify the relations in the published papers with machine learning ...

    Authors: Yueping Sun, Li Hou, Lu Qin, Yan Liu, Jiao Li and Qing Qian
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):234

    This article is part of a Supplement: Volume 19 Supplement 5

  12. De-identification is a critical technology to facilitate the use of unstructured clinical text while protecting patient privacy and confidentiality. The clinical natural language processing (NLP) community has...

    Authors: Xi Yang, Tianchen Lyu, Qian Li, Chih-Yin Lee, Jiang Bian, William R. Hogan and Yonghui Wu
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):232

    This article is part of a Supplement: Volume 19 Supplement 5

  13. The successful introduction of homomorphic encryption (HE) in clinical research holds promise for improving acceptance of data-sharing protocols, increasing sample sizes, and accelerating learning from real-wo...

    Authors: Silvia Paddock, Hamed Abedtash, Jacqueline Zummo and Samuel Thomas
    Citation: BMC Medical Informatics and Decision Making 2019 19:255
  14. This study explored the possible antecedents that will motivate hospital employees’ compliance with privacy policy related to electronic medical records (EMR) from a deterrence perspective. Further, we also in...

    Authors: Kuang-Ming Kuo, Paul C. Talley and Tain-Junn Cheng
    Citation: BMC Medical Informatics and Decision Making 2019 19:254
  15. Enabling patients to be active users of their own medical records may promote the delivery of safe, efficient care across settings. Patients are rarely involved in designing digital health record systems which...

    Authors: Leigh R. Warren, Matthew Harrison, Sonal Arora and Ara Darzi
    Citation: BMC Medical Informatics and Decision Making 2019 19:250
  16. The wide scale and severity of consequences of tobacco use, benefits derived from cessation, low rates of intervention by healthcare professionals, and new opportunities stemming from novel communications tech...

    Authors: J. F. Avila-Tomas, E. Olano-Espinosa, C. Minué-Lorenzo, F. J. Martinez-Suberbiola, B. Matilla-Pardo, M. E. Serrano-Serrano and E. Escortell-Mayor
    Citation: BMC Medical Informatics and Decision Making 2019 19:249
  17. Identifying dementia early in time, using real world data, is a public health challenge. As only two-thirds of people with dementia now ultimately receive a formal diagnosis in United Kingdom health systems an...

    Authors: Elizabeth Ford, Philip Rooney, Seb Oliver, Richard Hoile, Peter Hurley, Sube Banerjee, Harm van Marwijk and Jackie Cassell
    Citation: BMC Medical Informatics and Decision Making 2019 19:248
  18. Electronic health record (EHR) data are available for research in all UK nations and cross-nation comparative studies are becoming more common. All UK inpatient EHRs are based around episodes, but episode-base...

    Authors: Sarah Rees, Ashley Akbari, Huw Collins, Sze Chim Lee, Amanda Marchant, Arfon Rees, Daniel Thayer, Ting Wang, Sophie Wood and Ann John
    Citation: BMC Medical Informatics and Decision Making 2019 19:246
  19. Numerous studies have analyzed the effectiveness of electronic reminder interventions to improve different clinical conditions, and most have reported a small to moderate effect. Few studies, however, have ana...

    Authors: Ermengol Coma, Manuel Medina, Leonardo Méndez, Eduardo Hermosilla, Manuel Iglesias, Carmen Olmos and Sebastian Calero
    Citation: BMC Medical Informatics and Decision Making 2019 19:245
  20. This study used natural language processing (NLP) and machine learning (ML) techniques to identify reliable patterns from within research narrative documents to distinguish studies that complete successfully, ...

    Authors: Simon Geletta, Lendie Follett and Marcia Laugerman
    Citation: BMC Medical Informatics and Decision Making 2019 19:242
  21. Personal health records (PHRs) provide the opportunity for self-management support, enhancing communication between patients and caregivers, and maintaining and/or improving the quality of chronic disease mana...

    Authors: Floor Sieverink, Saskia Kelders, Annemarie Braakman-Jansen and Julia van Gemert-Pijnen
    Citation: BMC Medical Informatics and Decision Making 2019 19:241
  22. Neuropsychological tests (NPTs) are important tools for informing diagnoses of cognitive impairment (CI). However, interpreting NPTs requires specialists and is thus time-consuming. To streamline the applicati...

    Authors: Min Ju Kang, Sang Yun Kim, Duk L. Na, Byeong C. Kim, Dong Won Yang, Eun-Joo Kim, Hae Ri Na, Hyun Jeong Han, Jae-Hong Lee, Jong Hun Kim, Kee Hyung Park, Kyung Won Park, Seol-Heui Han, Seong Yoon Kim, Soo Jin Yoon, Bora Yoon…
    Citation: BMC Medical Informatics and Decision Making 2019 19:231
  23. Hospital electronic information management systems (HEIMS) are widely used in Ghana, and hence its performance must be carefully assessed. Nurses as clinical health personnel are the largest cluster of hospita...

    Authors: Lu Lin Zhou, Joseph Owusu-Marfo, Henry Asante Antwi, Maxwell Opuni Antwi, Arielle Doris Tetgoum Kachie and Sabina Ampon-Wireko
    Citation: BMC Medical Informatics and Decision Making 2019 19:230
  24. Demographic changes, increased life expectancy and the associated rise in chronic diseases pose challenges to public health care systems. Optimized treatment methods and integrated concepts of care are potenti...

    Authors: Alexander Lassnig, Theresa Rienmueller, Diether Kramer, Werner Leodolter, Christian Baumgartner and Joerg Schroettner
    Citation: BMC Medical Informatics and Decision Making 2019 19:229
  25. 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: V. Laengsri, W. Shoombuatong, W. Adirojananon, C. Nantasenamat, V. Prachayasittikul and P. Nuchnoi
    Citation: BMC Medical Informatics and Decision Making 2019 19:228

    The original article was published in BMC Medical Informatics and Decision Making 2019 19:212

  26. Following publication of the original article [1], the authors reported that the article erroneously stated that Dr. Ancker was affiliated with the Tehran University of Medical Sciences. Dr. Ancker is not affi...

    Authors: Jessica S. Ancker, Alison Edwards, Sarah Nosal, Diane Hauser, Elizabeth Mauer and Rainu Kaushal
    Citation: BMC Medical Informatics and Decision Making 2019 19:227

    The original article was published in BMC Medical Informatics and Decision Making 2017 17:36

  27. Electronic medical records (EMR) contain numerical data important for clinical outcomes research, such as vital signs and cardiac ejection fractions (EF), which tend to be embedded in narrative clinical notes....

    Authors: Tianrun Cai, Luwan Zhang, Nicole Yang, Kanako K. Kumamaru, Frank J. Rybicki, Tianxi Cai and Katherine P. Liao
    Citation: BMC Medical Informatics and Decision Making 2019 19:226
  28. There is limited information in Mexico - a middle-income country and a digital adopter with an important demographic bonus - regarding the potential use of technology and connectivity in health promotion among...

    Authors: Arturo Aguilar-Ye, Hortensia Reyes-Morales, Lourdes Campero and Nicéforo Garnelo-Bibiano
    Citation: BMC Medical Informatics and Decision Making 2019 19:225
  29. Obstructive sleep apnea (OSA) is a sleep disorder with a high prevalence in China. Standard diagnosis of OSA requires polysomnography (PSG). Currently, smart phone applications (apps) are widely used as an imp...

    Authors: Zhao-feng Xu, Xin Luo, Jianbo Shi and Yinyan Lai
    Citation: BMC Medical Informatics and Decision Making 2019 19:224
  30. The use of post-acute care (PAC) for cardiovascular conditions is highly variable across geographical regions. Although PAC benefits include lower readmission rates, better clinical outcomes, and lower mortali...

    Authors: Ineen Sultana, Madhav Erraguntla, Hye-Chung Kum, Dursun Delen and Mark Lawley
    Citation: BMC Medical Informatics and Decision Making 2019 19:223
  31. Global evidence suggests a range of benefits for introducing electronic health record (EHR) systems to improve patient care. However, implementing EHR within healthcare organisations is complex and, in the Uni...

    Authors: Carolyn McCrorie, Jonathan Benn, Owen Ashby Johnson and Arabella Scantlebury
    Citation: BMC Medical Informatics and Decision Making 2019 19:222
  32. The study aimed to assess the performance of a multidisciplinary-team diabetes care program called DIABETIMSS on glycemic control of type 2 diabetes (T2D) patients, by using available observational patient dat...

    Authors: Yue You, Svetlana V. Doubova, Diana Pinto-Masis, Ricardo Pérez-Cuevas, Víctor Hugo Borja-Aburto and Alan Hubbard
    Citation: BMC Medical Informatics and Decision Making 2019 19:221
  33. Interest in mHealth interventions, defined as the use of mobile phones to access healthcare is increasingly becoming popular globally. Given its technology-based applications, university students may be key cl...

    Authors: Prince Peprah, Emmanuel Mawuli Abalo, Williams Agyemang-Duah, Razak M Gyasi, Okwei Reforce, Julius Nyonyo, Godfred Amankwaa, Jones Amoako and Paulinus Kaaratoore
    Citation: BMC Medical Informatics and Decision Making 2019 19:220
  34. The use of digital technology in healthcare has been found to be useful for data collection, provision of health information and communications. Despite increasing use of medical mobile phone applications (app...

    Authors: Jenny Carter, Jane Sandall, Andrew H. Shennan and Rachel M. Tribe
    Citation: BMC Medical Informatics and Decision Making 2019 19:219
  35. Electronic health records (EHRs) are promising tools for routine care. These applications might not only enhance the interaction between patient and physician but also support therapy management. This is cruci...

    Authors: Toni Maria Klein, Matthias Augustin and Marina Otten
    Citation: BMC Medical Informatics and Decision Making 2019 19:218
  36. About 50% of patients with Crohn’s disease (CD) and about 20% of those with ulcerative colitis (UC) undergo surgery at some point during the course of the disease. The diagnostic validity of the Swedish Nation...

    Authors: Anders Forss, Pär Myrelid, Ola Olén, Åsa H. Everhov, Caroline Nordenvall, Jonas Halfvarson and Jonas F. Ludvigsson
    Citation: BMC Medical Informatics and Decision Making 2019 19:217
  37. Electronic health records (EHRs) with embedded clinical decision support systems (CDSSs) have the potential to improve healthcare delivery. This study was conducted to explore merits, features, and desiderata ...

    Authors: Ramzi Shawahna
    Citation: BMC Medical Informatics and Decision Making 2019 19:216
  38. Spatial epidemiological analyses primarily depend on spatially-indexed medical records. Some countries have devised ways of capturing patient-specific spatial details using ZIP codes, postcodes or personal num...

    Authors: Augustus Aturinde, Nakasi Rose, Mahdi Farnaghi, Gilbert Maiga, Petter Pilesjö and Ali Mansourian
    Citation: BMC Medical Informatics and Decision Making 2019 19:215
  39. Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. Recently, deep learning models...

    Authors: Rawan AlSaad, Qutaibah Malluhi, Ibrahim Janahi and Sabri Boughorbel
    Citation: BMC Medical Informatics and Decision Making 2019 19:214
  40. The paper introduces a deep learning-based approach for real-time detection and insights generation about one of the most prevalent chronic conditions in Australia - Pollen allergy. The popular social media pl...

    Authors: Jia Rong, Sandra Michalska, Sudha Subramani, Jiahua Du and Hua Wang
    Citation: BMC Medical Informatics and Decision Making 2019 19:208
  41. Smart pumps have been widely adopted but there is limited evidence to understand and support their use in pediatric populations. Our objective was to assess whether smart pumps are effective at reducing medica...

    Authors: Kristin R. Melton, Kristen Timmons, Kathleen E. Walsh, Jareen K. Meinzen-Derr and Eric Kirkendall
    Citation: BMC Medical Informatics and Decision Making 2019 19:213
  42. The hypochromic microcytic anemia (HMA) commonly found in Thailand are iron deficiency anemia (IDA) and thalassemia trait (TT). Accurate discrimination between IDA and TT is an important issue and better metho...

    Authors: V. Laengsri, W. Shoombuatong, W. Adirojananon, C. Nantasenamat, V. Prachayasittikul and P. Nuchnoi
    Citation: BMC Medical Informatics and Decision Making 2019 19:212

    The Correction to this article has been published in BMC Medical Informatics and Decision Making 2019 19:228

  43. Diabetes and cardiovascular disease are two of the main causes of death in the United States. Identifying and predicting these diseases in patients is the first step towards stopping their progression. We eval...

    Authors: An Dinh, Stacey Miertschin, Amber Young and Somya D. Mohanty
    Citation: BMC Medical Informatics and Decision Making 2019 19:211
  44. For an effective artificial pancreas (AP) system and an improved therapeutic intervention with continuous glucose monitoring (CGM), predicting the occurrence of hypoglycemia accurately is very important. While...

    Authors: Wonju Seo, You-Bin Lee, Seunghyun Lee, Sang-Man Jin and Sung-Min Park
    Citation: BMC Medical Informatics and Decision Making 2019 19:210
  45. Skilled assistance during childbirth is essential to reduce maternal deaths. However, in Ethiopia, which is among the six countries contributing to more than half of the global maternal deaths, the coverage of...

    Authors: Brook Tesfaye, Suleman Atique, Tariq Azim and Mihiretu M. Kebede
    Citation: BMC Medical Informatics and Decision Making 2019 19:209
  46. The global age-adjusted mortality rate related to atrial fibrillation (AF) registered a rapid growth in the last four decades, i.e., from 0.8 to 1.6 and 0.9 to 1.7 per 100,000 for men and women during 1990–201...

    Authors: Kwang-Sig Lee, Sunghoon Jung, Yeongjoon Gil and Ho Sung Son
    Citation: BMC Medical Informatics and Decision Making 2019 19:206
  47. Radiotherapy is a standard treatment option for breast cancer, but it may lead to significant late morbidity, including radiation heart damage. Breast irradiation performed individually in the supine or prone ...

    Authors: Ferenc Rárosi, Krisztina Boda, Zsuzsanna Kahán and Zoltán Varga
    Citation: BMC Medical Informatics and Decision Making 2019 19:204

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