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  1. Antimicrobial prophylaxis is an evidence-proven strategy for reducing procedure-related infections; however, measuring this key quality metric typically requires manual review, due to the way antimicrobial pro...

    Authors: Hillary J. Mull, Kelly Stolzmann, Emily Kalver, Marlena H. Shin, Marin L. Schweizer, Archana Asundi, Payal Mehta, Maggie Stanislawski and Westyn Branch-Elliman
    Citation: BMC Medical Informatics and Decision Making 2020 20:15
  2. The emergency department is a critical juncture in the trajectory of care of patients with serious, life-limiting illness. Implementation of a clinical decision support (CDS) tool automates identification of o...

    Authors: Audrey Tan, Mark Durbin, Frank R. Chung, Ada L. Rubin, Allison M. Cuthel, Jordan A. McQuilkin, Aram S. Modrek, Catherine Jamin, Nicholas Gavin, Devin Mann, Jordan L. Swartz, Jonathan S. Austrian, Paul A. Testa, Jacob D. Hill and Corita R. Grudzen
    Citation: BMC Medical Informatics and Decision Making 2020 20:13
  3. The Chinese assessment standards of the International Classification of Functioning, Disability and Health Rehabilitation Set is available now. It is coming to be used as a basic functional evaluation tool in ...

    Authors: Malan Zhang, Jiani Yu, Wei Shen, Yun Zhang, Yun Xiang, Xinting Zhang, Ziling Lin and Tiebin Yan
    Citation: BMC Medical Informatics and Decision Making 2020 20:12
  4. Tele-monitoring (TM) is remote monitoring of individuals via info-communication technology, enabling them and their relatives or care-providers to recognize their health status conveniently. TM will be success...

    Authors: David Yang Ern Sin, Xiaoxuan Guo, Dayna Wei Wei Yong, Tian Yu Qiu, Peter Kirm Seng Moey, Muller-Riemenschneider Falk and Ngiap Chuan Tan
    Citation: BMC Medical Informatics and Decision Making 2020 20:11
  5. 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
  6. Height and weight data from electronic health records are increasingly being used to estimate the prevalence of childhood obesity. Here, we aim to assess the selection bias due to missing weight and height dat...

    Authors: Carmen Sayon-Orea, Conchi Moreno-Iribas, Josu Delfrade, Manuela Sanchez-Echenique, Pilar Amiano, Eva Ardanaz, Javier Gorricho, Garbiñe Basterra, Marian Nuin and Marcela Guevara
    Citation: BMC Medical Informatics and Decision Making 2020 20:9
  7. 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
  8. 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
  9. Mobile health applications (mHealth apps) are increasingly being used to perform tasks that are conventionally performed by general practitioners (GPs), such as those involved in promoting health, preventing d...

    Authors: Apichai Wattanapisit, Chin Hai Teo, Sanhapan Wattanapisit, Emylia Teoh, Wing Jun Woo and Chirk Jenn Ng
    Citation: BMC Medical Informatics and Decision Making 2020 20:5
  10. In classification and diagnostic testing, the receiver-operator characteristic (ROC) plot and the area under the ROC curve (AUC) describe how an adjustable threshold causes changes in two types of error: false...

    Authors: André M. Carrington, Paul W. Fieguth, Hammad Qazi, Andreas Holzinger, Helen H. Chen, Franz Mayr and Douglas G. Manuel
    Citation: BMC Medical Informatics and Decision Making 2020 20:4
  11. We used the Surveillance, Epidemiology, and End Results (SEER) database to develop and validate deep survival neural network machine learning (ML) algorithms to predict survival following a spino-pelvic chondr...

    Authors: Sung Mo Ryu, Sung Wook Seo and Sun-Ho Lee
    Citation: BMC Medical Informatics and Decision Making 2020 20:3
  12. As healthcare facilities in Low- and Middle-Income Countries adopt digital health systems to improve hospital administration and patient care, it is important to understand the adoption process and assess the ...

    Authors: Naomi Muinga, Steve Magare, Jonathan Monda, Mike English, Hamish Fraser, John Powell and Chris Paton
    Citation: BMC Medical Informatics and Decision Making 2020 20:2
  13. Targeted client communication (TCC) using text messages can inform, motivate and remind pregnant and postpartum women of timely utilization of care. The mixed results of the effectiveness of TCC interventions ...

    Authors: Binyam Bogale, Kjersti Mørkrid, Brian O’Donnell, Buthaina Ghanem, Itimad Abu Ward, Khadija Abu Khader, Mervett Isbeih, Michael Frost, Mohammad Baniode, Taghreed Hijaz, Tamara Awwad, Yousef Rabah and J. Frederik Frøen
    Citation: BMC Medical Informatics and Decision Making 2020 20:1
  14. Although Internet-based interventions (IBIs) have been around for two decades, uptake has been slow. Increasing the acceptability of IBIs among end users may increase uptake. In this study, we explored the fac...

    Authors: Sherald Sanchez, Farah Jindani, Jing Shi, Mark van der Maas, Sylvia Hagopian, Robert Murray and Nigel Turner
    Citation: BMC Medical Informatics and Decision Making 2019 19:290
  15. Patient stratification is a critical task in clinical decision making since it can allow physicians to choose treatments in a personalized way. Given the increasing availability of electronic medical records (...

    Authors: Kishan Rama, Helena Canhão, Alexandra M. Carvalho and Susana Vinga
    Citation: BMC Medical Informatics and Decision Making 2019 19:289
  16. There are often multiple lesions in breast magnetic resonance imaging (MRI) reports and radiologists usually focus on describing the index lesion that is most crucial to clinicians in determining the managemen...

    Authors: Yi Liu, Qing Liu, Chao Han, Xiaodong Zhang and Xiaoying Wang
    Citation: BMC Medical Informatics and Decision Making 2019 19:288
  17. 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
  18. 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
  19. The accelerated growth of elderly population is creating a heavy burden to the healthcare system in many developed countries and regions. Electrocardiogram (ECG) analysis has been recognized as effective appro...

    Authors: Xiaomao Fan, Yang Zhao, Hailiang Wang and Kwok Leung Tsui
    Citation: BMC Medical Informatics and Decision Making 2019 19:285
  20. Community-acquired pneumonia (CAP) is one of the leading causes of morbidity and mortality in the USA. Our objective was to assess the predictive value on critical illness and disposition of a sequential Bayes...

    Authors: Amado Alejandro Baez, Laila Cochon and Jose Maria Nicolas
    Citation: BMC Medical Informatics and Decision Making 2019 19:284
  21. To foster responsible data sharing in health research, ethical governance complementary to the EU General Data Protection Regulation is necessary. A governance framework for Big Data-driven research platforms ...

    Authors: S. Kalkman, M. Mostert, N. Udo-Beauvisage, J. J. van Delden and G. J. van Thiel
    Citation: BMC Medical Informatics and Decision Making 2019 19:283
  22. Family history (FH) information, including family members, side of family of family members (i.e., maternal or paternal), living status of family members, observations (diseases) of family members, etc., is ve...

    Authors: Xue Shi, Dehuan Jiang, Yuanhang Huang, Xiaolong Wang, Qingcai Chen, Jun Yan and Buzhou Tang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 10):277

    This article is part of a Supplement: Volume 19 Supplement 10

  23. Family history information (FHI) described in unstructured electronic health records (EHRs) is a valuable information source for patient care and scientific researches. Since FHI is usually described in the fo...

    Authors: Hong-Jie Dai
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 10):257

    This article is part of a Supplement: Volume 19 Supplement 10

  24. The medical community uses a variety of data standards for both clinical and research reporting needs. ISO 11179 Common Data Elements (CDEs) represent one such standard that provides robust data point definiti...

    Authors: Robinette Renner, Shengyu Li, Yulong Huang, Ada Chaeli van der Zijp-Tan, Shaobo Tan, Dongqi Li, Mohan Vamsi Kasukurthi, Ryan Benton, Glen M. Borchert, Jingshan Huang and Guoqian Jiang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 7):276

    This article is part of a Supplement: Volume 19 Supplement 7

  25. Internet of things is fast becoming the norm in everyday life, and integrating the Internet into medical treatment, which is increasing day by day, is of high utility to both clinical doctors and patients. Whi...

    Authors: Bin Ma, Chunxiao Li, Zhaolong Wu, Yulong Huang, Ada Chaeli van der Zijp-Tan, Shaobo Tan, Dongqi Li, Ada Fong, Chandan Basetty, Glen M. Borchert, Ryan Benton, Bin Wu and Jingshan Huang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 7):275

    This article is part of a Supplement: Volume 19 Supplement 7

  26. Text mining and natural language processing of clinical text, such as notes from electronic health records, requires specific consideration of the specialized characteristics of these texts. Deep learning meth...

    Authors: Rebecka Weegar, Alicia Pérez, Arantza Casillas and Maite Oronoz
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 7):274

    This article is part of a Supplement: Volume 19 Supplement 7

  27. Clinical Named Entity Recognition is to find the name of diseases, body parts and other related terms from the given text. Because Chinese language is quite different with English language, the machine cannot ...

    Authors: Yifei Wang, Sophia Ananiadou and Jun’ichi Tsujii
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 7):273

    This article is part of a Supplement: Volume 19 Supplement 7

  28. Developing a stroke health-education mobile app (SHEMA) and examining its effectiveness on improvement of knowledge of stroke risk factors and health-related quality of life (HRQOL) in patients with stroke.

    Authors: Yi-No Kang, Hsiu-Nien Shen, Chia-Yun Lin, Glyn Elwyn, Szu-Chi Huang, Tsung-Fu Wu and Wen-Hsuan Hou
    Citation: BMC Medical Informatics and Decision Making 2019 19:282
  29. 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
  30. Botulinum toxin (BT) injection is a new treatment for spasticity with hemiplegia after stroke. How a patient decides to receive BT injections after becoming aware of the treatment remains unclear. In this expl...

    Authors: Sawako Arai, Yuko Fukase, Akira Okii, Yoshimi Suzukamo and Toshimitsu Suga
    Citation: BMC Medical Informatics and Decision Making 2019 19:280
  31. With the advent of new high-throughput electron microscopy techniques such as serial block-face scanning electron microscopy (SBF-SEM) and focused ion-beam scanning electron microscopy (FIB-SEM) biomedical sci...

    Authors: Afshin Khadangi, Eric Hanssen and Vijay Rajagopal
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 6):272

    This article is part of a Supplement: Volume 19 Supplement 6

  32. Nucleus Accumbens (NAc) is a vital brain region for the process of reward and stress, whereas microRNA plays a crucial role in depression pathology. However, the abnormality of NAc miRNA expression during the ...

    Authors: Weichen Song, Yifeng Shen, Yanhua Zhang, Sufang Peng, Ran Zhang, Ailing Ning, Huafang Li, Xia Li, Guan Ning Lin and Shunying Yu
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 6):271

    This article is part of a Supplement: Volume 19 Supplement 6

  33. Automatic vascular segmentation in X-ray angiographic image sequence is of crucial interest, for instance, for better quantifying coronary arteries in diagnostic and interventional procedures.

    Authors: Shuang Song, Chenbing Du, Ying Chen, Danni Ai, Hong Song, Yong Huang, Yongtian Wang and Jian Yang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 6):270

    This article is part of a Supplement: Volume 19 Supplement 6

  34. A collection of disease-associated data contributes to study the association between diseases. Discovering closely related diseases plays a crucial role in revealing their common pathogenic mechanisms. This mi...

    Authors: Lei Deng, Danyi Ye, Junmin Zhao and Jingpu Zhang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 6):269

    This article is part of a Supplement: Volume 19 Supplement 6

  35. As a physiological signal, EEG data cannot be subjectively changed or hidden. Compared with other physiological signals, EEG signals are directly related to human cortical activities with excellent temporal re...

    Authors: Ahmed Fares, Sheng-hua Zhong and Jianmin Jiang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 6):268

    This article is part of a Supplement: Volume 19 Supplement 6

  36. Diagnosis aims to predict the future health status of patients according to their historical electronic health records (EHR), which is an important yet challenging task in healthcare informatics. Existing diag...

    Authors: Fenglong Ma, Yaqing Wang, Houping Xiao, Ye Yuan, Radha Chitta, Jing Zhou and Jing Gao
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 6):267

    This article is part of a Supplement: Volume 19 Supplement 6

  37. Globally, the cases of diabetes mellitus (diabetes) have increased in the past three decades, and it is recorded as one of the leading cause of death. This epidemic is a metabolic condition where the body cann...

    Authors: Igbe Tobore, Jingzhen Li, Abhishek Kandwal, Liu Yuhang, Zedong Nie and Lei Wang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 6):266

    This article is part of a Supplement: Volume 19 Supplement 6

  38. Many genetic variants have been reported from sequencing projects due to decreasing experimental costs. Compared to the current typical paradigm, read mapping incorporating existing variants can improve the pe...

    Authors: Hongzhe Guo, Bo Liu, Dengfeng Guan, Yilei Fu and Yadong Wang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 6):265

    This article is part of a Supplement: Volume 19 Supplement 6

  39. Traditional Chinese medicine (TCM) is a highly important complement to modern medicine and is widely practiced in China and in many other countries. The work of Chinese medicine is subject to the two factors o...

    Authors: Xintian Chen, Chunyang Ruan, Yanchun Zhang and Huijuan Chen
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 6):264

    This article is part of a Supplement: Volume 19 Supplement 6

  40. Sequence alignment is a way of arranging sequences (e.g., DNA, RNA, protein, natural language, financial data, or medical events) to identify the relatedness between two or more sequences and regions of simila...

    Authors: Ming Huang, Nilay D. Shah and Lixia Yao
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 6):263

    This article is part of a Supplement: Volume 19 Supplement 6

  41. Adverse drug reaction (ADR) is a major burden for patients and healthcare industry. Early and accurate detection of potential ADRs can help to improve drug safety and reduce financial costs. Post-market sponta...

    Authors: Ruoqi Liu and Ping Zhang
    Citation: BMC Medical Informatics and Decision Making 2019 19:279
  42. Behaviour change interventions targeting physical activity, diet, sleep and sedentary behaviour of teenagers show promise when delivered through smartphones. However, to date there is no evidence of effectiven...

    Authors: Elisa Puigdomenech, Anne Martin, Alexandra Lang, Fulvio Adorni, Santiago Felipe Gomez, Brian McKinstry, Federica Prinelli, Laura Condon, Rajeeb Rashid, Maurizio Caon, Sarah Atkinson, Claudio L. Lafortuna, Valentina Ciociola, Janet Hanley, Lucy McCloughan, Conxa Castell…
    Citation: BMC Medical Informatics and Decision Making 2019 19:278

    The Correction to this article has been published in BMC Medical Informatics and Decision Making 2021 21:337

  43. Electronic health records (EHRs) provide possibilities to improve patient care and facilitate clinical research. However, there are many challenges faced by the applications of EHRs, such as temporality, high ...

    Authors: Tong Ruan, Liqi Lei, Yangming Zhou, Jie Zhai, Le Zhang, Ping He and Ju Gao
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 8):259

    This article is part of a Supplement: Volume 19 Supplement 8

  44. Chronic obstructive pulmonary disease (COPD) is a progressive lung disease that is classified into stages based on disease severity. We aimed to characterize the time to progression prior to death in patients ...

    Authors: Chunlei Tang, Joseph M. Plasek, Haohan Zhang, Min-Jeoung Kang, Haokai Sheng, Yun Xiong, David W. Bates and Li Zhou
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 8):258

    This article is part of a Supplement: Volume 19 Supplement 8

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

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

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

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

  46. Handwriting represents one of the major symptom in Parkinson’s Disease (PD) patients. The computer-aided analysis of the handwriting allows for the identification of promising patterns that might be useful in ...

    Authors: Giacomo Donato Cascarano, Claudio Loconsole, Antonio Brunetti, Antonio Lattarulo, Domenico Buongiorno, Giacomo Losavio, Eugenio Di Sciascio and Vitoantonio Bevilacqua
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 9):252

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

  47. In order to better help doctors make decision in the clinical setting, research is necessary to connect electronic health record (EHR) with the biomedical literature. Pseudo Relevance Feedback (PRF) is a kind ...

    Authors: Min Pan, Yue Zhang, Qiang Zhu, Bo Sun, Tingting He and Xingpeng Jiang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 9):251

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

  48. The automatic segmentation of kidneys in medical images is not a trivial task when the subjects undergoing the medical examination are affected by Autosomal Dominant Polycystic Kidney Disease (ADPKD). Several ...

    Authors: Vitoantonio Bevilacqua, Antonio Brunetti, Giacomo Donato Cascarano, Andrea Guerriero, Francesco Pesce, Marco Moschetta and Loreto Gesualdo
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 9):244

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

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