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

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

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

    Content type: Research article

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

    Authors: Florian Kohlmayer, Ronald Lautenschläger and Fabian Prasser

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

    Content type: Debate

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

  11. 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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  12. 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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  13. 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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  14. 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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  15. 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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  16. 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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  17. 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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  18. 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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  19. 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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  20. 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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  21. 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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  22. 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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  23. 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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  24. 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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  25. 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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  27. 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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  28. 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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  29. 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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  30. 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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  31. 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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  32. 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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  33. 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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  34. 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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  35. 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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  36. 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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  37. 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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  38. 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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  39. 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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  40. 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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  41. 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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  42. 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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  43. 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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  44. 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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  45. 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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  46. 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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  47. 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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  48. 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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  49. 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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  50. 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

    Published on:

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