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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. Various methods based on k-anonymity have been proposed for publishing medical data while preserving privacy. However, the k-anonymity property assumes that adversaries possess fixed background knowledge. Althoug...

    Authors: Hyukki Lee and Yon Dohn Chung

    Citation: BMC Medical Informatics and Decision Making 2020 20:155

    Content type: Research article

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  2. For real-time monitoring of hospital patients, high-quality inference of patients’ health status using all information available from clinical covariates and lab test results is essential to enable successful ...

    Authors: Li-Fang Cheng, Bianca Dumitrascu, Gregory Darnell, Corey Chivers, Michael Draugelis, Kai Li and Barbara E Engelhardt

    Citation: BMC Medical Informatics and Decision Making 2020 20:152

    Content type: Technical Advance

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  3. Semantic interoperability is essential for improving data quality and sharing. The ISO/IEC 11179 Metadata Registry (MDR) standard has been highlighted as a solution for standardizing and registering clinical d...

    Authors: Hye Hyeon Kim, Yu Rang Park, Suehyun Lee and Ju Han Kim

    Citation: BMC Medical Informatics and Decision Making 2020 20:147

    Content type: Technical advance

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  4. As a kind of widely distributed disease in China, acquired immune deficiency syndrome (AIDS) has been quickly growing each year, become a serious problem and caused serious damage to the life and health of peo...

    Authors: Zeming Li and Yanning Li

    Citation: BMC Medical Informatics and Decision Making 2020 20:143

    Content type: Research article

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  5. Transient ischemic attack (TIA) is a brief episode of neurological dysfunction resulting from cerebral ischemia not associated with permanent cerebral infarction. TIA is associated with high diagnostic errors ...

    Authors: Alia Stanciu, Mihai Banciu, Alireza Sadighi, Kyle A. Marshall, Neil R. Holland, Vida Abedi and Ramin Zand

    Citation: BMC Medical Informatics and Decision Making 2020 20:112

    Content type: Research article

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  6. The essential proteins in protein networks play an important role in complex cellular functions and in protein evolution. Therefore, the identification of essential proteins in a network can help to explain th...

    Authors: Caiyan Dai, Ju He, Kongfa Hu and Youwei Ding

    Citation: BMC Medical Informatics and Decision Making 2020 20:110

    Content type: Research article

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  7. Predictive patient stratification is greatly emerging, because it allows us to prospectively identify which patients will benefit from what interventions before their condition worsens. In the biomedical resea...

    Authors: Thanh-Trung Giang, Thanh-Phuong Nguyen and Dang-Hung Tran

    Citation: BMC Medical Informatics and Decision Making 2020 20:108

    Content type: Research article

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  8. Patients increasingly turn to search engines and online content before, or in place of, talking with a health professional. Low quality health information, which is common on the internet, presents risks to th...

    Authors: Laura Kinkead, Ahmed Allam and Michael Krauthammer

    Citation: BMC Medical Informatics and Decision Making 2020 20:104

    Content type: Research Article

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  9. The aim of the German Medical Informatics Initiative is to establish a national infrastructure for integrating and sharing health data. To this, Data Integration Centers are set up at university medical center...

    Authors: Raffael Bild, Martin Bialke, Karoline Buckow, Thomas Ganslandt, Kristina Ihrig, Roland Jahns, Angela Merzweiler, Sybille Roschka, Björn Schreiweis, Sebastian Stäubert, Sven Zenker and Fabian Prasser

    Citation: BMC Medical Informatics and Decision Making 2020 20:103

    Content type: Technical advance

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  10. Patient experience surveys often include free-text responses. Analysis of these responses is time-consuming and often underutilized. This study examined whether Natural Language Processing (NLP) techniques cou...

    Authors: Simone A. Cammel, Marit S. De Vos, Daphne van Soest, Kristina M. Hettne, Fred Boer, Ewout W. Steyerberg and Hileen Boosman

    Citation: BMC Medical Informatics and Decision Making 2020 20:97

    Content type: Research article

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  11. Health information systems are increasingly sophisticated and developing them is a challenge for software developers. Software engineers usually make use of UML as a standard model language that allows definin...

    Authors: M. A. Olivero, F. J. Domínguez-Mayo, C. L. Parra-Calderón, M. J. Escalona and A. Martínez-García

    Citation: BMC Medical Informatics and Decision Making 2020 20:96

    Content type: Research article

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  12. Systematic, automated methods for monitoring physician performance are necessary if outlying behavior is to be detected promptly and acted on. In the Michigan Urological Surgery Improvement Collaborative (MUSI...

    Authors: Michael Inadomi, Karandeep Singh, Ji Qi, Rodney Dunn, Susan Linsell, Brian Denton, Patrick Hurley, Eduardo Kleer, James Montie and Khurshid R. Ghani

    Citation: BMC Medical Informatics and Decision Making 2020 20:89

    Content type: Research article

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  13. Geriatric patients frequently undergo emergency general surgery and accrue a greater risk of postoperative complications and fatal outcomes than the general population. It is highly relevant to develop the mos...

    Authors: Yang Cao, Gary A. Bass, Rebecka Ahl, Arvid Pourlotfi, Håkan Geijer, Scott Montgomery and Shahin Mohseni

    Citation: BMC Medical Informatics and Decision Making 2020 20:86

    Content type: Research article

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  14. Accumulating evidence has linked environmental exposure, such as ambient air pollution and meteorological factors, to the development and severity of cardiovascular diseases (CVDs), resulting in increased heal...

    Authors: Hang Qiu, Lin Luo, Ziqi Su, Li Zhou, Liya Wang and Yucheng Chen

    Citation: BMC Medical Informatics and Decision Making 2020 20:83

    Content type: Research article

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  15. Automated de-identification methods for removing protected health information (PHI) from the source notes of the electronic health record (EHR) rely on building systems to recognize mentions of PHI in text, bu...

    Authors: Brihat Sharma, Dmitriy Dligach, Kristin Swope, Elizabeth Salisbury-Afshar, Niranjan S. Karnik, Cara Joyce and Majid Afshar

    Citation: BMC Medical Informatics and Decision Making 2020 20:79

    Content type: Research article

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  16. Data quality assessment presents a challenge for research using coded administrative health data. The objective of this study is to develop and validate a set of coding association rules for coded diagnostic d...

    Authors: Mingkai Peng, Sangmin Lee, Adam G. D’Souza, Chelsea T. A. Doktorchik and Hude Quan

    Citation: BMC Medical Informatics and Decision Making 2020 20:75

    Content type: Research article

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  17. Drug label, or packaging insert play a significant role in all the operations from production through drug distribution channels to the end consumer. Image of the label also called Display Panel or label could...

    Authors: Xiangwen Liu, Joe Meehan, Weida Tong, Leihong Wu, Xiaowei Xu and Joshua Xu

    Citation: BMC Medical Informatics and Decision Making 2020 20:68

    Content type: Research article

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  18. The International Classification of Diseases, 10th Revision (ICD-10) has been widely used to describe the diagnosis information of patients. Automatic ICD-10 coding is important because manually assigning code...

    Authors: Lingling Zhou, Cheng Cheng, Dong Ou and Hao Huang

    Citation: BMC Medical Informatics and Decision Making 2020 20:67

    Content type: Research article

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  19. In this study, we focus on building a fine-grained entity annotation corpus with the corresponding annotation guideline of traditional Chinese medicine (TCM) clinical records. Our aim is to provide a basis for...

    Authors: Tingting Zhang, Yaqiang Wang, Xiaofeng Wang, Yafei Yang and Ying Ye

    Citation: BMC Medical Informatics and Decision Making 2020 20:64

    Content type: Research article

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  20. Clinical prediction tasks such as patient mortality, length of hospital stay, and disease diagnosis are highly important in critical care research. The existing studies for clinical prediction mainly used simp...

    Authors: Chonghui Guo, Menglin Lu and Jingfeng Chen

    Citation: BMC Medical Informatics and Decision Making 2020 20:48

    Content type: Research Article

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  21. The detection of Alzheimer’s Disease (AD) in its formative stages, especially in Mild Cognitive Impairments (MCI), has the potential of helping the clinicians in understanding the condition. The literature rev...

    Authors: Harsh Bhasin and Ramesh Kumar Agrawal

    Citation: BMC Medical Informatics and Decision Making 2020 20:37

    Content type: Research article

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  22. Acute Kidney Injury (AKI) is common among inpatients. Severe AKI increases all-cause mortality especially in critically ill patients. Older patients are more at risk of AKI because of the declined renal functi...

    Authors: Yi-Shian Chen, Che-Yi Chou and Arbee L.P. Chen

    Citation: BMC Medical Informatics and Decision Making 2020 20:36

    Content type: Research article

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  23. Modern data driven medical research promises to provide new insights into the development and course of disease and to enable novel methods of clinical decision support. To realize this, machine learning model...

    Authors: Johanna Eicher, Raffael Bild, Helmut Spengler, Klaus A. Kuhn and Fabian Prasser

    Citation: BMC Medical Informatics and Decision Making 2020 20:29

    Content type: Software

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  24. A common problem in machine learning applications is availability of data at the point of decision making. The aim of the present study was to use routine data readily available at admission to predict aspects...

    Authors: J. Wolff, A. Gary, D. Jung, C. Normann, K. Kaier, H. Binder, K. Domschke, A. Klimke and M. Franz

    Citation: BMC Medical Informatics and Decision Making 2020 20:21

    Content type: Research article

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  25. Data masking is an inborn defect of measures of disproportionality in adverse drug reactions (ADRs) signal detection. Many previous studies can be roughly classified into three categories: data removal, regres...

    Authors: Jian-Xiang Wei, Yue Ding, Ming Li and Jun Sun

    Citation: BMC Medical Informatics and Decision Making 2020 20:18

    Content type: Research article

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  26. Cardiovascular diseases kill approximately 17 million people globally every year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) occurs when the heart cannot pump enou...

    Authors: Davide Chicco and Giuseppe Jurman

    Citation: BMC Medical Informatics and Decision Making 2020 20:16

    Content type: Research Article

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  27. Automated machine-learning systems are able to de-identify electronic medical records, including free-text clinical notes. Use of such systems would greatly boost the amount of data available to researchers, y...

    Authors: Tzvika Hartman, Michael D. Howell, Jeff Dean, Shlomo Hoory, Ronit Slyper, Itay Laish, Oren Gilon, Danny Vainstein, Greg Corrado, Katherine Chou, Ming Jack Po, Jutta Williams, Scott Ellis, Gavin Bee, Avinatan Hassidim, Rony Amira…

    Citation: BMC Medical Informatics and Decision Making 2020 20:14

    Content type: Research article

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  28. Cloud storage facilities (CSF) has become popular among the internet users. There is limited data on CSF usage among university students in low middle-income countries including Sri Lanka. In this study we pre...

    Authors: Samankumara Hettige, Eshani Dasanayaka and Dileepa Senajith Ediriweera

    Citation: BMC Medical Informatics and Decision Making 2020 20:10

    Content type: Research article

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  29. 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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  30. 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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  31. 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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  32. 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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  33. 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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  34. 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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  35. 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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  36. 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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  37. 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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  38. 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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  39. 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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  40. 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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  41. 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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  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

    Content type: Technical advance

    Published on:

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

  43. 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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  44. 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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  45. 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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  46. 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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  47. 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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  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

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