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  1. Administrative healthcare databases are widespread and are often standardized with regard to their content and data coding, thus they can be used also as data sources for surveillance and epidemiological resea...

    Authors: Dino Gibertoni, Claudio Voci, Marica Iommi, Benedetta D’Ercole, Marcora Mandreoli, Antonio Santoro and Elena Mancini
    Citation: BMC Medical Informatics and Decision Making 2020 20:185
  2. Quantifying soccer players’ performance using different types of technologies helps coaches in making tactical decisions and maintaining players’ health. Little is known about the relation between the performa...

    Authors: Jassim Almulla, Abdulrahman Takiddin and Mowafa Househ
    Citation: BMC Medical Informatics and Decision Making 2020 20:184
  3. Stakeholder engagement is being increasingly recognised as an important way to achieving impact in public health. The WorkHORSE (Working Health Outcomes Research Simulation Environment) project was designed to co...

    Authors: Ffion Lloyd-Williams, Lirije Hyseni, Maria Guzman-Castillo, Chris Kypridemos, Brendan Collins, Simon Capewell, Ellen Schwaller and Martin O’Flaherty
    Citation: BMC Medical Informatics and Decision Making 2020 20:182
  4. Chronic patients persistently seek for health information on the internet for medication information seeking, nutrition, disease management, information regarding disease preventive actions and so on. Consumer...

    Authors: Kirubel Biruk Shiferaw, Binyam Chakilu Tilahun, Berhanu Fikadie Endehabtu, Monika Knudsen Gullslett and Shegaw Anagaw Mengiste
    Citation: BMC Medical Informatics and Decision Making 2020 20:181
  5. User satisfaction with PACS is considered as one of the important criteria for assessing success in using PACS. The objective of this study was to determine the level of user satisfaction with PACS and to comp...

    Authors: Reza Abbasi, Monireh Sadeqi Jabali, Reza Khajouei and Hamidreza Tadayon
    Citation: BMC Medical Informatics and Decision Making 2020 20:180
  6. Malignant pleural effusion (MPE) is a common, serious problem predominantly seen in metastatic lung and breast cancer and malignant pleural mesothelioma. Recurrence of malignant pleural effusion is common, and...

    Authors: Cheryl Grindell, Angela Tod, Remi Bec, Daniel Wolstenholme, Rahul Bhatnagar, Parthipan Sivakumar, Anna Morley, Jayne Holme, Judith Lyons, Maryam Ahmed, Susan Jackson, Deirdre Wallace, Farinaz Noorzad, Meera Kamalanathan, Liju Ahmed and Mathew Evison
    Citation: BMC Medical Informatics and Decision Making 2020 20:179
  7. More information is often thought to improve medical decision-making, which may lead to test overuse. This study assesses which out of 15 laboratory tests contribute to diagnosing the underlying cause of anaem...

    Authors: Michelle M. A. Kip, Martijn L. J. Oonk, Mark-David Levin, Annemarie Schop, Patrick J. E. Bindels, Ron Kusters and Hendrik Koffijberg
    Citation: BMC Medical Informatics and Decision Making 2020 20:178
  8. A number of resources, every year, being spent to tackle early detection of cardiac abnormalities which is one of the leading causes of deaths all over the Globe. The challenges for healthcare systems includes...

    Authors: Muhammad Shabaan, Kaleem Arshid, Muhammad Yaqub, Feng Jinchao, M. Sultan Zia, Giridhar Reddy Bojja, Muazzam Iftikhar, Usman Ghani, Loknath Sai Ambati and Rizwan Munir
    Citation: BMC Medical Informatics and Decision Making 2020 20:177

    The Correction to this article has been published in BMC Medical Informatics and Decision Making 2020 20:217

  9. Poor adherence to long-term recombinant human growth hormone (r-hGH) treatment can lead to suboptimal clinical outcomes; consequently, supporting and monitoring adherence is a crucial part of patient managemen...

    Authors: Ekaterina Koledova, Vincenzo Tornincasa and Paula van Dommelen
    Citation: BMC Medical Informatics and Decision Making 2020 20:176
  10. Informational discontinuity can have far reaching consequences like medical errors, increased re-hospitalization rates and adverse events among others. Thus the holy grail of seamless informational continuity ...

    Authors: Naveen R. Gowda, Atul Kumar, Sanjay K. Arya and Vikas H
    Citation: BMC Medical Informatics and Decision Making 2020 20:175
  11. Research using linked routine population-based data collected for non-research purposes has increased in recent years because they are a rich and detailed source of information. The objective of this study is ...

    Authors: Daniela Almeida, David Gorender, Maria Yury Ichihara, Samila Sena, Luan Menezes, George C. G. Barbosa, Rosimeire L. Fiaccone, Enny S. Paixão, Robespierre Pita and Mauricio L. Barreto
    Citation: BMC Medical Informatics and Decision Making 2020 20:173
  12. Shared decision-making improves the quality of patient care. Unfortunately, shared decision-making is not yet common practice among vascular surgeons. Thus, decision support tools were developed to assist vasc...

    Authors: S. M. L. de Mik, F. E. Stubenrouch, D. A. Legemate, R. Balm and D. T. Ubbink
    Citation: BMC Medical Informatics and Decision Making 2020 20:172
  13. The exact risk of developing QTc-prolongation when using a combination of QTc-prolonging drugs is still unknown, making it difficult to interpret these QT drug-drug interactions (QT-DDIs). A tool to identify h...

    Authors: Florine A. Berger, Heleen van der Sijs, Matthijs L. Becker, Teun van Gelder and Patricia M. L. A. van den Bemt
    Citation: BMC Medical Informatics and Decision Making 2020 20:171
  14. Parent-clinician shared decision making is the recommended model for the care of premature infants; thus, clinicians provide prenatal prematurity counseling to parents in the event of a mother’s hospitalizatio...

    Authors: Nicole M. Rau, Mir A. Basir and Kathryn E. Flynn
    Citation: BMC Medical Informatics and Decision Making 2020 20:169
  15. “Artificial intelligence” (AI) is often referred to as “augmented human intelligence” (AHI). The latter term implies that computers support—rather than replace—human decision-making. It is unclear whether the ...

    Authors: Santiago Romero-Brufau, Kirk D. Wyatt, Patricia Boyum, Mindy Mickelson, Matthew Moore and Cheristi Cognetta-Rieke
    Citation: BMC Medical Informatics and Decision Making 2020 20:167
  16. Building and validating electronic algorithms to identify patients with specific disease profiles using health data is becoming increasingly important to disease surveillance and population health management. The...

    Authors: Rachael Morkem, Kenneth Handelman, John A. Queenan, Richard Birtwhistle and David Barber
    Citation: BMC Medical Informatics and Decision Making 2020 20:166
  17. Surgical resection of pheochromocytoma may lead to high risk factors for intraoperative hemodynamic instability (IHD), which can be life-threatening. This study aimed to investigate the risk factors that could...

    Authors: Yueyang Zhao, Li Fang, Lei Cui and Song Bai
    Citation: BMC Medical Informatics and Decision Making 2020 20:165
  18. Worldwide the rate of unplanned pregnancies is more than 40%. Identifying women at risk of pregnancy can help prevent negative outcomes and also reduce healthcare costs of potential complications. It can also ...

    Authors: Lucía Cea Soriano, Alex Asiimwe, Mieke Van Hemelrijck, Cecilia Bosco and Luis A. García Rodríguez
    Citation: BMC Medical Informatics and Decision Making 2020 20:164
  19. Unequivocal identification of patients is a precondition for a safe medical journey through different information systems (ISs) and software applications that are communicating and exchanging interoperable dat...

    Authors: Raffaella Vaccaroli, Frédéric Markus, Samuel Danhardt, Heiko Zimmermann, Francois Wisniewski, Pascale Lucas and Hervé Barge
    Citation: BMC Medical Informatics and Decision Making 2020 20:163
  20. One of the most challenging tasks for bladder cancer diagnosis is to histologically differentiate two early stages, non-invasive Ta and superficially invasive T1, the latter of which is associated with a signi...

    Authors: Peng-Nien Yin, Kishan KC, Shishi Wei, Qi Yu, Rui Li, Anne R. Haake, Hiroshi Miyamoto and Feng Cui
    Citation: BMC Medical Informatics and Decision Making 2020 20:162
  21. Delay in identifying deterioration in hospitalised patients is associated with delayed admission to an intensive care unit (ICU) and poor outcomes. For the HAVEN project (HICF ref.: HICF-R9–524), we have devel...

    Authors: Simarjot S. Dahella, James S. Briggs, Paul Coombes, Nazli Farajidavar, Paul Meredith, Timothy Bonnici, Julie L. Darbyshire and Peter J. Watkinson
    Citation: BMC Medical Informatics and Decision Making 2020 20:161
  22. The healthcare sector is an interesting target for fraudsters. The availability of a great amount of data makes it possible to tackle this issue with the adoption of data mining techniques, making the auditing...

    Authors: Michela Carlotta Massi, Francesca Ieva and Emanuele Lettieri
    Citation: BMC Medical Informatics and Decision Making 2020 20:160
  23. The electronic patient record (EPR) has been introduced into nursing homes in order to facilitate documentation practices such as assessment and care planning, which play an integral role in the provision of d...

    Authors: Kate Shiells, Angie Alejandra Diaz Baquero, Olga Štěpánková and Iva Holmerová
    Citation: BMC Medical Informatics and Decision Making 2020 20:159
  24. Particularly in the context of severe diseases like cancer, many patients wish to include caregivers in the planning of treatment and care. Many caregivers like to be involved but feel insufficiently enabled. ...

    Authors: Aline Weis, Sabrina Pohlmann, Regina Poss-Doering, Beate Strauss, Charlotte Ullrich, Helene Hofmann, Dominik Ose, Eva C. Winkler, Joachim Szecsenyi and Michel Wensing
    Citation: BMC Medical Informatics and Decision Making 2020 20:158
  25. The promises of improved health care and health research through data-intensive applications rely on a growing amount of health data. At the core of large-scale data integration efforts, clinical data warehous...

    Authors: Elena Pavlenko, Daniel Strech and Holger Langhof
    Citation: BMC Medical Informatics and Decision Making 2020 20:157
  26. Despite the numerous healthcare smartphone applications for self-management of diabetes, patients often fail to use these applications consistently due to various limitations, including difficulty in inputting...

    Authors: Sung Woon Park, Gyuri Kim, You-Cheol Hwang, Woo Je Lee, Hyunjin Park and Jae Hyeon Kim
    Citation: BMC Medical Informatics and Decision Making 2020 20:156
  27. Evidence-based Clinical Decision Support Systems (CDSSs) usually obtain clinical evidences from randomized controlled trials based on coarse-grained groups. Individuals who are beyond the scope of the original...

    Authors: Junyi Yang, Liang Xiao and Kangning Li
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):138

    This article is part of a Supplement: Volume 20 Supplement 3

  28. Circular RNAs (circRNAs) are those RNA molecules that lack the poly (A) tails, which present the closed-loop structure. Recent studies emphasized that some circRNAs imply different functions from canonical tra...

    Authors: Yidan Wang, Xuanping Zhang, Tao Wang, Jinchun Xing, Zhun Wu, Wei Li and Jiayin Wang
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):137

    This article is part of a Supplement: Volume 20 Supplement 3

  29. Bladder cancer (BC) is regarded as one of the most fatal cancer around the world. Nevertheless, there still lack of sufficient markers to predict the prognosis of BC patients. Herein, we aim to establish a pro...

    Authors: Xiaolong Zhang, Meng Zhang, Xuanping Zhang, Xiaoyan Zhu and Jiayin Wang
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):136

    This article is part of a Supplement: Volume 20 Supplement 3

  30. Hepatocellular carcinoma is one of the most general malignant neoplasms in adults with high mortality. Mining relative medical knowledge from rapidly growing text data and integrating it with other existing bi...

    Authors: Nan Li, Zhihao Yang, Ling Luo, Lei Wang, Yin Zhang, Hongfei Lin and Jian Wang
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):135

    This article is part of a Supplement: Volume 20 Supplement 3

  31. It is of utmost importance to investigate novel therapies for cancer, as it is a major cause of death. In recent years, immunotherapies, especially those against immune checkpoints, have been developed and bro...

    Authors: Yuyu Zheng, Xiangyu Meng, Pierre Zweigenbaum, Lingling Chen and Jingbo Xia
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):133

    This article is part of a Supplement: Volume 20 Supplement 3

  32. With China experiencing unprecedented economic development and social change over the past three decades, Chinese policy makers and health care professionals have come to view mental health as an important out...

    Authors: Wenyan Tan, Haicheng Lin, Baoxin Lei, Aihua Ou, Zehui He, Ning Yang, Fujun Jia, Heng Weng and Tianyong Hao
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):132

    This article is part of a Supplement: Volume 20 Supplement 3

  33. The interpretability of results predicted by the machine learning models is vital, especially in the critical fields like healthcare. With the increasingly adoption of electronic healthcare records (EHR) by th...

    Authors: Peipei Chen, Wei Dong, Jinliang Wang, Xudong Lu, Uzay Kaymak and Zhengxing Huang
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):131

    This article is part of a Supplement: Volume 20 Supplement 3

  34. The social Q&A community quickly becomes a popular platform for consumers to find health information because of its convenience and interactivity.

    Authors: Wang Zhao, Peixin Lu, Siwei Yu and Long Lu
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):130

    This article is part of a Supplement: Volume 20 Supplement 3

  35. With the rapid development of sequencing technologies, collecting diverse types of cancer omics data become more cost-effective. Many computational methods attempted to represent and fuse multiple omics into a...

    Authors: Kaiwen Tan, Weixian Huang, Jinlong Hu and Shoubin Dong
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):129

    This article is part of a Supplement: Volume 20 Supplement 3

  36. Nowadays, the latent power of technology, which can offer innovative resolutions to disease diagnosis, has awakened high-level anticipation in the community of patients as well as professionals. An easy-to-use...

    Authors: Fan Guo, Weiqing Li, Xin Zhao, Junfeng Qiu and Yuxiang Mai
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):128

    This article is part of a Supplement: Volume 20 Supplement 3

  37. In the few studies of clinical experience available, cigarette smoking may be associated with ischemic heart disease and acute coronary events, which can be reflected in the electrocardiogram (ECG). However, t...

    Authors: Kuo-Kun Tseng, Jiaqian Li, Yih-Jing Tang, Ching Wen Yang and Fang-Ying Lin
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):127

    This article is part of a Supplement: Volume 20 Supplement 3

  38. Cardiogenic stroke has increasing morbidity in China and brought economic burden to patient families. In cardiogenic stroke diagnosis, echocardiograph examination is one of the most important examinations. Son...

    Authors: Lu Qin, Xiaowei Xu, Lingling Ding, Zixiao Li and Jiao Li
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):126

    This article is part of a Supplement: Volume 20 Supplement 3

  39. To provide satisfying answers, medical QA system has to understand the intentions of the users’ questions precisely. For medical intent classification, it requires high-quality datasets to train a deep-learnin...

    Authors: Nan Chen, Xiangdong Su, Tongyang Liu, Qizhi Hao and Ming Wei
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):125

    This article is part of a Supplement: Volume 20 Supplement 3

  40. Reinforcement learning (RL) provides a promising technique to solve complex sequential decision making problems in healthcare domains. Recent years have seen a great progress of applying RL in addressing decis...

    Authors: Chao Yu, Guoqi Ren and Yinzhao Dong
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):124

    This article is part of a Supplement: Volume 20 Supplement 3

  41. Electronic medical records contain a variety of valuable medical information for patients. So, when we are able to recognize and extract risk factors for disease from EMRs of patients with cardiovascular disea...

    Authors: Zhichang Zhang, Yanlong Qiu, Xiaoli Yang and Minyu Zhang
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):123

    This article is part of a Supplement: Volume 20 Supplement 3

  42. The increasing global cancer incidence corresponds to serious health impact in countries worldwide. Knowledge-powered health system in different languages would enhance clinicians’ healthcare practice, patient...

    Authors: Hetong Ma, Feihong Yang, Jiansong Ren, Ni Li, Min Dai, Xuwen Wang, An Fang, Jiao Li, Qing Qian and Jie He
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):122

    This article is part of a Supplement: Volume 20 Supplement 3

  43. Blood cultures are often performed to detect patients who has a serious illness without infections and patients with bloodstream infections. Early positive blood culture prediction is important, as bloodstream...

    Authors: Ming Cheng, Xiaolei Zhao, Xianfei Ding, Jianbo Gao, Shufeng Xiong and Yafeng Ren
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):121

    This article is part of a Supplement: Volume 20 Supplement 3

  44. Although clinical guidelines provide the best practice for medical activities, there are some limitations in using clinical guidelines to assistant decision-making in practical application, such as long update...

    Authors: Haifeng Xu, Jianfei Pang, Xi Yang, Mei Li and Dongsheng Zhao
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):120

    This article is part of a Supplement: Volume 20 Supplement 3

  45. Deep learning based on segmentation models have been gradually applied in biomedical images and achieved state-of-the-art performance for 3D biomedical segmentation. However, most of existing biomedical segmen...

    Authors: Xibin Jia, Yunfeng Liu, Zhenghan Yang and Dawei Yang
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):119

    This article is part of a Supplement: Volume 20 Supplement 3

  46. A semi-supervised model is proposed for extracting clinical terms of Traditional Chinese Medicine using feature words.

    Authors: Liangliang Liu, Xiaojing Wu, Hui Liu, Xinyu Cao, Haitao Wang, Hongwei Zhou and Qi Xie
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 3):118

    This article is part of a Supplement: Volume 20 Supplement 3

  47. 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
  48. 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

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