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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. Stroke severity is an important predictor of patient outcomes and is commonly measured with the National Institutes of Health Stroke Scale (NIHSS) scores. Because these scores are often recorded as free text i...

    Authors: Emily Kogan, Kathryn Twyman, Jesse Heap, Dejan Milentijevic, Jennifer H. Lin and Mark Alberts

    Citation: BMC Medical Informatics and Decision Making 2020 20:8

    Content type: Research article

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  2. The ubiquity of electronic health records (EHR) offers an opportunity to observe trajectories of laboratory results and vital signs over long periods of time. This study assessed the value of risk factor traje...

    Authors: Gyorgy J. Simon, Kevin A. Peterson, M. Regina Castro, Michael S. Steinbach, Vipin Kumar and Pedro J. Caraballo

    Citation: BMC Medical Informatics and Decision Making 2020 20:6

    Content type: Research article

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  3. To examine the association between the medical imaging utilization and information related to patients’ socioeconomic, demographic and clinical factors during the patients’ ED visits; and to develop predictive...

    Authors: Xingyu Zhang, M. Fernanda Bellolio, Pau Medrano-Gracia, Konrad Werys, Sheng Yang and Prashant Mahajan

    Citation: BMC Medical Informatics and Decision Making 2019 19:287

    Content type: Research article

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  4. Fetal heart rate (FHR) monitoring is a screening tool used by obstetricians to evaluate the fetal state. Because of the complexity and non-linearity, a visual interpretation of FHR signals using common guideli...

    Authors: Zhidong Zhao, Yanjun Deng, Yang Zhang, Yefei Zhang, Xiaohong Zhang and Lihuan Shao

    Citation: BMC Medical Informatics and Decision Making 2019 19:286

    Content type: Research article

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  5. Supervised machine learning algorithms have been a dominant method in the data mining field. Disease prediction using health data has recently shown a potential application area for these methods. This study a...

    Authors: Shahadat Uddin, Arif Khan, Md Ekramul Hossain and Mohammad Ali Moni

    Citation: BMC Medical Informatics and Decision Making 2019 19:281

    Content type: Research article

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  6. 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

    Content type: Technical Advance

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  7. 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

    Content type: Research article

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  8. 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

    Content type: Research article

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  9. 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

    Content type: Research article

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  10. 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

    Content type: Research article

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  11. 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

    Content type: Software

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  12. 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

    Content type: Research article

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  13. 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

    Content type: Research Article

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  14. 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

    Content type: Technical advance

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

  15. 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

    Content type: Research Article

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  16. 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

    Content type: Research article

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  17. 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

    Content type: Research article

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  18. Time of death estimation in humans for the benefit of forensic medicine has been successfully approached by Henssge, who modelled body cooling based on measurements of Marshall and Hoare. Thereby, body and amb...

    Authors: Wolf Schweitzer and Michael J. Thali

    Citation: BMC Medical Informatics and Decision Making 2019 19:201

    Content type: Technical Advance

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  19. Breast cancer causes hundreds of thousands of deaths each year worldwide. The early stage diagnosis and treatment can significantly reduce the mortality rate. However, the traditional manual diagnosis needs in...

    Authors: Chuang Zhu, Fangzhou Song, Ying Wang, Huihui Dong, Yao Guo and Jun Liu

    Citation: BMC Medical Informatics and Decision Making 2019 19:198

    Content type: Research Article

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  20. Several heart failure (HF) risk models exist, however, most of them perform poorly when applied to real-world situations. This study aimed to develop a convenient and efficient risk model to identify patients ...

    Authors: Bo-yu Tan, Jun-yuan Gu, Hong-yan Wei, Li Chen, Su-lan Yan and Nan Deng

    Citation: BMC Medical Informatics and Decision Making 2019 19:193

    Content type: Research article

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  21. 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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  22. 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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  23. 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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  24. 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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  25. 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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  26. 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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  27. 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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  28. 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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  29. 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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  30. 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

  31. 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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  32. 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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  33. 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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  34. 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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  35. 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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  36. 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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  37. 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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  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. 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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  40. 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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  41. 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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  42. 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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  43. 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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  44. 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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  45. 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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  46. 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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  47. 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

    Published on:

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