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Standards, technology, machine learning, and modeling

Section edited by Andreas Holzinger

This section considers manuscripts that investigate data analysis, data mining and machine learning in healthcare systems, disease prediction, forecasting and modeling, as well as studies in advanced information and data management systems, and knowledge bases.

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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

    Published on:

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

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

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  12. COPD is a highly heterogeneous disease composed of different phenotypes with different aetiological and prognostic profiles and current classification systems do not fully capture this heterogeneity. In this s...

    Authors: Maria Pikoula, Jennifer Kathleen Quint, Francis Nissen, Harry Hemingway, Liam Smeeth and Spiros Denaxas

    Citation: BMC Medical Informatics and Decision Making 2019 19:86

    Content type: Research article

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  13. Breast cancer is one of the most common diseases in women worldwide. Many studies have been conducted to predict the survival indicators, however most of these analyses were predominantly performed using basic...

    Authors: Mogana Darshini Ganggayah, Nur Aishah Taib, Yip Cheng Har, Pietro Lio and Sarinder Kaur Dhillon

    Citation: BMC Medical Informatics and Decision Making 2019 19:48

    Content type: Research article

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  14. Heterogeneous healthcare instance data can hardly be integrated without harmonizing its schema-level metadata. Many medical research projects and organizations use metadata repositories to edit, store and reus...

    Authors: H. Ulrich, J. Kern, D. Tas, A. K. Kock-Schoppenhauer, F. Ückert, J. Ingenerf and M. Lablans

    Citation: BMC Medical Informatics and Decision Making 2019 19:45

    Content type: Software

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  15. Clinical data synthesis aims at generating realistic data for healthcare research, system implementation and training. It protects patient confidentiality, deepens our understanding of the complexity in health...

    Authors: Junqiao Chen, David Chun, Milesh Patel, Epson Chiang and Jesse James

    Citation: BMC Medical Informatics and Decision Making 2019 19:44

    Content type: Research article

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  16. Medications are frequently used for treating schizophrenia, however, anti-psychotic drug use is known to lead to cases of pneumonia. The purpose of our study is to build a model for predicting hospital-acquire...

    Authors: Kuang Ming Kuo, Paul C. Talley, Chi Hsien Huang and Liang Chih Cheng

    Citation: BMC Medical Informatics and Decision Making 2019 19:42

    Content type: Research article

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  17. Services for the preclinical development and evaluation of cardiovascular implant devices (CVIDs) is a new industry. However, there is still no indicator system for quality evaluation. Our aim is to construct ...

    Authors: Yongchun Cui, Fuliang Luo, Boqing Yang, Bin Li, Qi Zhang, Gopika Das, Guangxin Yue, Jiajie Li, Yue Tang and Xin Wang

    Citation: BMC Medical Informatics and Decision Making 2019 19:37

    Content type: Research article

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  18. Life expectancy is one of the most important factors in end-of-life decision making. Good prognostication for example helps to determine the course of treatment and helps to anticipate the procurement of healt...

    Authors: Merijn Beeksma, Suzan Verberne, Antal van den Bosch, Enny Das, Iris Hendrickx and Stef Groenewoud

    Citation: BMC Medical Informatics and Decision Making 2019 19:36

    Content type: Research article

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  19. Increasing life expectancy results in more elderly people struggling with age related diseases and functional conditions. This poses huge challenges towards establishing new approaches for maintaining health a...

    Authors: Andreas Philipp Hassler, Ernestina Menasalvas, Francisco José García-García, Leocadio Rodríguez-Mañas and Andreas Holzinger

    Citation: BMC Medical Informatics and Decision Making 2019 19:33

    Content type: Research article

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  20. Vast volumes of data, coded through hierarchical terminologies (e.g., International Classification of Diseases, Tenth Revision–Clinical Modification [ICD10-CM], Medical Subject Headings [MeSH]), are generated ...

    Authors: Xia Jing, Matthew Emerson, David Masters, Matthew Brooks, Jacob Buskirk, Nasseef Abukamail, Chang Liu, James J. Cimino, Jay Shubrook, Sonsoles De Lacalle, Yuchun Zhou and Vimla L. Patel

    Citation: BMC Medical Informatics and Decision Making 2019 19:31

    Content type: Software

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  21. Clusters of under-vaccinated children are emerging in a number of states in the United States due to rising rates of vaccine hesitancy and refusal. As the measles outbreaks in California and other states in 20...

    Authors: Jose Cadena, David Falcone, Achla Marathe and Anil Vullikanti

    Citation: BMC Medical Informatics and Decision Making 2019 19:28

    Content type: Research article

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  22. Medication trend studies show the changes of medication over the years and may be replicated using a clinical Data Warehouse (CDW). Even nowadays, a lot of the patient information, like medication data, in the...

    Authors: Georg Dietrich, Jonathan Krebs, Leon Liman, Georg Fette, Maximilian Ertl, Mathias Kaspar, Stefan Störk and Frank Puppe

    Citation: BMC Medical Informatics and Decision Making 2019 19:15

    Content type: Research article

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  23. Adverse drug events (ADEs) as well as other preventable adverse events in the hospital setting incur a yearly monetary cost of approximately $3.5 billion, in the United States alone. Therefore, it is of paramo...

    Authors: Francesco Bagattini, Isak Karlsson, Jonathan Rebane and Panagiotis Papapetrou

    Citation: BMC Medical Informatics and Decision Making 2019 19:7

    Content type: Research article

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  24. The Personal Patient Profile-Prostate (P3P) is a web-based decision support system for men newly diagnosed with localized prostate cancer that has demonstrated efficacy in reducing decisional conflict. Our obj...

    Authors: Leslie S. Wilson, Traci M. Blonquist, Fangxin Hong, Barbara Halpenny, Seth Wolpin, Peter Chang, Christopher P. Filson, Viraj A. Master, Martin G. Sanda, Gary W. Chien, Randy A. Jones, Tracey L. Krupski and Donna L. Berry

    Citation: BMC Medical Informatics and Decision Making 2019 19:6

    Content type: Research article

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  25. Main adverse cardiac events (MACE) are essentially composite endpoints for assessing safety and efficacy of treatment processes of acute coronary syndrome (ACS) patients. Timely prediction of MACE is highly va...

    Authors: Huilong Duan, Zhoujian Sun, Wei Dong and Zhengxing Huang

    Citation: BMC Medical Informatics and Decision Making 2019 19:5

    Content type: Research article

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  26. Automatic clinical text classification is a natural language processing (NLP) technology that unlocks information embedded in clinical narratives. Machine learning approaches have been shown to be effective fo...

    Authors: Yanshan Wang, Sunghwan Sohn, Sijia Liu, Feichen Shen, Liwei Wang, Elizabeth J. Atkinson, Shreyasee Amin and Hongfang Liu

    Citation: BMC Medical Informatics and Decision Making 2019 19:1

    Content type: Research article

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  27. Nowadays, trendy research in biomedical sciences juxtaposes the term ‘precision’ to medicine and public health with companion words like big data, data science, and deep learning. Technological advancements pe...

    Authors: Mattia Prosperi, Jae S. Min, Jiang Bian and François Modave

    Citation: BMC Medical Informatics and Decision Making 2018 18:139

    Content type: Debate

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  28. Predicting progression from Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD) is an utmost open issue in AD-related research. Neuropsychological assessment has proven to be useful in identifying MCI ...

    Authors: Telma Pereira, Francisco L. Ferreira, Sandra Cardoso, Dina Silva, Alexandre de Mendonça, Manuela Guerreiro and Sara C. Madeira

    Citation: BMC Medical Informatics and Decision Making 2018 18:137

    Content type: Research article

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  29. Systems science methods such as dynamic simulation modelling are well suited to address questions about public health policy as they consider the complexity, context and dynamic nature of system-wide behaviour...

    Authors: Louise Freebairn, Jo-An Atkinson, Paul M. Kelly, Geoff McDonnell and Lucie Rychetnik

    Citation: BMC Medical Informatics and Decision Making 2018 18:131

    Content type: Research article

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  30. Extracting primary care information in terms of Patient/Problem, Intervention, Comparison and Outcome, known as PICO elements, is difficult as the volume of medical information expands and the health semantics...

    Authors: Samir Chabou and Michal Iglewski

    Citation: BMC Medical Informatics and Decision Making 2018 18:128

    Content type: Research article

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  31. To characterize the regional and national variation in prescribing patterns in the Medicare Part D program using dimensional reduction visualization methods.

    Authors: Alexander Rosenberg, Christopher Fucile, Robert J. White, Melissa Trayhan, Samir Farooq, Caroline M. Quill, Lisa A. Nelson, Samuel J. Weisenthal, Kristen Bush and Martin S. Zand

    Citation: BMC Medical Informatics and Decision Making 2018 18:103

    Content type: Research article

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  32. Cost effectiveness research is emerging in the chronic kidney disease (CKD) research field. Especially, an individual-level state transition model (microsimulation) is widely used for these researches. Some re...

    Authors: Shusuke Hiragi, Hiroshi Tamura, Rei Goto and Tomohiro Kuroda

    Citation: BMC Medical Informatics and Decision Making 2018 18:94

    Content type: Research article

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  33. Treatment with effective antiretroviral therapy (ART) lowers morbidity and mortality among HIV positive individuals. Effective highly active antiretroviral therapy (HAART) should lead to undetectable viral loa...

    Authors: Kuteesa R. Bisaso, Susan A. Karungi, Agnes Kiragga, Jackson K. Mukonzo and Barbara Castelnuovo

    Citation: BMC Medical Informatics and Decision Making 2018 18:77

    Content type: Research article

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  34. Systematized Nomenclature of Medicine—Clinical Terms (SNOMED CT, hereafter abbreviated SCT) is a comprehensive medical terminology used for standardizing the storage, retrieval, and exchange of electronic heal...

    Authors: Shaker El-Sappagh, Francesco Franda, Farman Ali and Kyung-Sup Kwak

    Citation: BMC Medical Informatics and Decision Making 2018 18:76

    Content type: Research article

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  35. Kidney stone (KS) disease has high, increasing prevalence in the United States and poses a massive economic burden. Diagnostics algorithms of KS only use a few variables with a limited sensitivity and specific...

    Authors: Zhaoyi Chen, Victoria Y. Bird, Rupam Ruchi, Mark S. Segal, Jiang Bian, Saeed R. Khan, Marie-Carmelle Elie and Mattia Prosperi

    Citation: BMC Medical Informatics and Decision Making 2018 18:72

    Content type: Research article

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  36. Text mining (TM) methods have been used extensively to extract relations and events from the literature. In addition, TM techniques have been used to extract various types or dimensions of interpretative informat...

    Authors: Matthew Shardlow, Riza Batista-Navarro, Paul Thompson, Raheel Nawaz, John McNaught and Sophia Ananiadou

    Citation: BMC Medical Informatics and Decision Making 2018 18:46

    Content type: Research article

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  37. Heart failure is one of the leading causes of hospitalization in the United States. Advances in big data solutions allow for storage, management, and mining of large volumes of structured and semi-structured d...

    Authors: Sara Bersche Golas, Takuma Shibahara, Stephen Agboola, Hiroko Otaki, Jumpei Sato, Tatsuya Nakae, Toru Hisamitsu, Go Kojima, Jennifer Felsted, Sujay Kakarmath, Joseph Kvedar and Kamal Jethwani

    Citation: BMC Medical Informatics and Decision Making 2018 18:44

    Content type: Research article

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  38. Hospital crowding is a rising problem, effective predicting and detecting managment can helpful to reduce crowding. Our team has successfully proposed a hybrid model combining both the autoregressive integrate...

    Authors: Lingling Zhou, Ping Zhao, Dongdong Wu, Cheng Cheng and Hao Huang

    Citation: BMC Medical Informatics and Decision Making 2018 18:39

    Content type: Research article

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  39. A scoping review to characterize the literature on the use of conversations in social media as a potential source of data for detecting adverse events (AEs) related to health products.

    Authors: Andrea C. Tricco, Wasifa Zarin, Erin Lillie, Serena Jeblee, Rachel Warren, Paul A. Khan, Reid Robson, Ba’ Pham, Graeme Hirst and Sharon E. Straus

    Citation: BMC Medical Informatics and Decision Making 2018 18:38

    Content type: Research article

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  40. Monoclonal antibodies blocking the Cytotoxic T-lymphocyte antigen 4 (CTLA-4) receptor have revolutionized the field of anti-cancer therapy for the last few years. The human T-cell-based immune responses are mo...

    Authors: Aravindhan Ganesan, Theinmozhi Arulraj, Tahir Choulli and Khaled H. Barakat

    Citation: BMC Medical Informatics and Decision Making 2018 18:37

    Content type: Research article

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  41. Alzheimer’s Disease (AD) is a neurodegenaritive disorder characterized by a progressive dementia, for which actually no cure is known. An early detection of patients affected by AD can be obtained by analyzing...

    Authors: Giulia Fiscon, Emanuel Weitschek, Alessio Cialini, Giovanni Felici, Paola Bertolazzi, Simona De Salvo, Alessia Bramanti, Placido Bramanti and Maria Cristina De Cola

    Citation: BMC Medical Informatics and Decision Making 2018 18:35

    Content type: Research article

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  42. Medical coding is used for a variety of activities, from observational studies to hospital billing. However, comorbidities tend to be under-reported by medical coders. The aim of this study was to develop an a...

    Authors: Emmanuelle Sylvestre, Guillaume Bouzillé, Emmanuel Chazard, Cécil His-Mahier, Christine Riou and Marc Cuggia

    Citation: BMC Medical Informatics and Decision Making 2018 18:9

    Content type: Research article

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  43. Traditional survey methods are limited in the study of hidden populations due to the hard to access properties, including lack of a sampling frame, sensitivity issue, reporting error, small sample size, etc. T...

    Authors: Chuchu Liu and Xin Lu

    Citation: BMC Medical Informatics and Decision Making 2018 18:2

    Content type: Research article

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  44. Claims data are currently widely used as source data in asthma studies. However, the insufficient information in claims data related to level of asthma severity may negatively impact study findings. The presen...

    Authors: Tsung-Hsien Yu, Pin-Kuei Fu and Yu-Chi Tung

    Citation: BMC Medical Informatics and Decision Making 2017 17:177

    Content type: Research article

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  45. Prior studies have demonstrated that cardiorespiratory fitness (CRF) is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques ...

    Authors: Sherif Sakr, Radwa Elshawi, Amjad M. Ahmed, Waqas T. Qureshi, Clinton A. Brawner, Steven J. Keteyian, Michael J. Blaha and Mouaz H. Al-Mallah

    Citation: BMC Medical Informatics and Decision Making 2017 17:174

    Content type: Research article

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  46. Antimicrobial Resistance is threatening our ability to treat common infectious diseases and overuse of antimicrobials to treat human infections in hospitals is accelerating this process. Clinical Decision Supp...

    Authors: Bernard Hernandez, Pau Herrero, Timothy Miles Rawson, Luke S. P. Moore, Benjamin Evans, Christofer Toumazou, Alison H. Holmes and Pantelis Georgiou

    Citation: BMC Medical Informatics and Decision Making 2017 17:168

    Content type: Research article

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  47. Autism Spectrum Disorder (ASD) is one of the fastest-growing developmental disorders in the United States. It was hypothesized that variations in the placental chorionic surface vascular network (PCSVN) struct...

    Authors: Jen-Mei Chang, Hui Zeng, Ruxu Han, Ya-Mei Chang, Ruchit Shah, Carolyn M. Salafia, Craig Newschaffer, Richard K. Miller, Philip Katzman, Jack Moye, Margaret Fallin, Cheryl K. Walker and Lisa Croen

    Citation: BMC Medical Informatics and Decision Making 2017 17:162

    Content type: Research article

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  48. Since the emergence of electronic health records, nursing information is increasingly being recorded and stored digitally. Several studies have shown that a wide range of nursing information is not interoperab...

    Authors: R. A. M. M. Kieft, E. M. Vreeke, E. M. de Groot, P. A. Volkert, A. L. Francke and D. M. J. Delnoij

    Citation: BMC Medical Informatics and Decision Making 2017 17:158

    Content type: Research article

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  49. The medical subdomain of a clinical note, such as cardiology or neurology, is useful content-derived metadata for developing machine learning downstream applications. To classify the medical subdomain of a not...

    Authors: Wei-Hung Weng, Kavishwar B. Wagholikar, Alexa T. McCray, Peter Szolovits and Henry C. Chueh

    Citation: BMC Medical Informatics and Decision Making 2017 17:155

    Content type: Research article

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  1. As the amount of information in electronic health care systems increases, data operations get more complicated and time-consuming. Intensive Care platforms require a timely processing of data retrievals to gua...

    Authors: Kristof Steurbaut, Steven Latré, Johan Decruyenaere and Filip De Turck

    Citation: BMC Medical Informatics and Decision Making 2013 13:120

    Content type: Research article

    Published on:

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