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  1. Chinese word segmentation (CWS) and part-of-speech (POS) tagging are two fundamental tasks of Chinese text processing. They are usually preliminary steps for lots of Chinese natural language processing (NLP) t...

    Authors: Ying Xiong, Zhongmin Wang, Dehuan Jiang, Xiaolong Wang, Qingcai Chen, Hua Xu, Jun Yan and Buzhou Tang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):66
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  2. The Named Entity Recognition (NER) task as a key step in the extraction of health information, has encountered many challenges in Chinese Electronic Medical Records (EMRs). Firstly, the casual use of Chinese a...

    Authors: Xiaoling Cai, Shoubin Dong and Jinlong Hu
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):65
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  3. With the rapid spread of electronic medical records and the arrival of medical big data era, the application of natural language processing technology in biomedicine has become a hot research topic.

    Authors: Bin Ji, Rui Liu, Shasha Li, Jie Yu, Qingbo Wu, Yusong Tan and Jiaju Wu
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):64
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  4. Extracting relations between bio-entities from biomedical literature is often a challenging task and also an essential step towards biomedical knowledge expansion. The BioCreative community has organized a sha...

    Authors: Suwen Liu, Yifan Shao, Longhua Qian and Guodong Zhou
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):63
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  5. Gender information frequently exists in the eligibility criteria of clinical trial text as essential information for participant population recruitment. Particularly, current eligibility criteria text contains...

    Authors: Boyu Chen, Hao Jin, Zhiwen Yang, Yingying Qu, Heng Weng and Tianyong Hao
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):62
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  6. Major adverse cardiac event (MACE) prediction plays a key role in providing efficient and effective treatment strategies for patients with acute coronary syndrome (ACS) during their hospitalizations. Existing ...

    Authors: Danqing Hu, Wei Dong, Xudong Lu, Huilong Duan, Kunlun He and Zhengxing Huang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):61
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  7. Reinforcement learning (RL) provides a promising technique to solve complex sequential decision making problems in health care domains. However, existing studies simply apply naive RL algorithms in discovering...

    Authors: Chao Yu, Yinzhao Dong, Jiming Liu and Guoqi Ren
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):60
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  8. Drug development is an expensive and time-consuming process. Literature-based discovery has played a critical role in drug development and may be a supplementary method to help scientists speed up the discover...

    Authors: Di Zhao, Jian Wang, Shengtian Sang, Hongfei Lin, Jiabin Wen and Chunmei Yang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):59
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  9. Learning distributional representation of clinical concepts (e.g., diseases, drugs, and labs) is an important research area of deep learning in the medical domain. However, many existing relevant methods do no...

    Authors: Yang Xiang, Jun Xu, Yuqi Si, Zhiheng Li, Laila Rasmy, Yujia Zhou, Firat Tiryaki, Fang Li, Yaoyun Zhang, Yonghui Wu, Xiaoqian Jiang, Wenjin Jim Zheng, Degui Zhi, Cui Tao and Hua Xu
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):58
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  10. Reinforcement learning (RL) provides a promising technique to solve complex sequential decision making problems in health care domains. To ensure such applications, an explicit reward function encoding domain ...

    Authors: Chao Yu, Jiming Liu and Hongyi Zhao
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):57
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  11. Electronic Medical Records(EMRs) contain much medical information about patients. Medical named entity extracting from EMRs can provide value information to support doctors’ decision making. The research on in...

    Authors: Yan Gao, Lei Gu, Yefeng Wang, Yandong Wang and Feng Yang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):56
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  12. Electronic medical records (EMRs) contain a variety of valuable medical concepts and relations. The ability to recognize relations between medical concepts described in EMRs enables the automatic processing of...

    Authors: Zhichang Zhang, Tong Zhou, Yu Zhang and Yali Pang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):55
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  13. Medical event detection in narrative clinical notes of electronic health records (EHRs) is a task designed for reading text and extracting information. Most of the previous work of medical event detection trea...

    Authors: Xuesi Zhou, Haoqi Xiong, Sihan Zeng, Xiangling Fu and Ji Wu
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):54
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  14. The traditional Chinese Medicine Language System (TCMLS) is a large-scale terminology system, developed from 2002 on by the Institute of Information of Traditional Chinese Medicine (IITCM). Until now, more tha...

    Authors: Hai Long, Yan Zhu, Lirong Jia, Bo Gao, Jing Liu, Lihong Liu and Heinrich Herre
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):53
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  15. Medical and clinical question answering (QA) is highly concerned by researchers recently. Though there are remarkable advances in this field, the development in Chinese medical domain is relatively backward. I...

    Authors: Junqing He, Mingming Fu and Manshu Tu
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):52
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  16. Social media plays a more and more important role in the research of health and healthcare due to the fast development of internet communication and information exchange. This paper conducts a bibliometric ana...

    Authors: Xieling Chen, Yonghui Lun, Jun Yan, Tianyong Hao and Heng Weng
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):50
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  17. Diabetes has become one of the hot topics in life science researches. To support the analytical procedures, researchers and analysts expend a mass of labor cost to collect experimental data, which is also erro...

    Authors: Fan Gong, Yilei Chen, Haofen Wang and Hao Lu
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):49
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  18. Malnutrition is one of the most important reasons for child mortality in developing countries, especially during the first 5 years of life. We set out to systematically review evaluations of interventions that...

    Authors: Navisa Seyyedi, Bahlol Rahimi, Hamid Reza Farrokh Eslamlou, Toomas Timpka and Hadi Lotfnezhad Afshar
    Citation: BMC Medical Informatics and Decision Making 2019 19:83
    Content type: Research article Published on:

  19. Accurate information in provider directories are vital in health care including health information exchange, health benefits exchange, quality reporting, and in the reimbursement and delivery of care. Maintain...

    Authors: Matthew J. Cook, Lixia Yao and Xiaoyan Wang
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):80
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  20. Twitter messages (tweets) contain various types of topics in our daily life, which include health-related topics. Analysis of health-related tweets would help us understand health conditions and concerns encou...

    Authors: Son Doan, Elly W. Yang, Sameer S. Tilak, Peter W. Li, Daniel S. Zisook and Manabu Torii
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):79
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  21. This paper presents a portable phenotyping system that is capable of integrating both rule-based and statistical machine learning based approaches.

    Authors: Himanshu Sharma, Chengsheng Mao, Yizhen Zhang, Haleh Vatani, Liang Yao, Yizhen Zhong, Luke Rasmussen, Guoqian Jiang, Jyotishman Pathak and Yuan Luo
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):78
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  22. A shareable repository of clinical notes is critical for advancing natural language processing (NLP) research, and therefore a goal of many NLP researchers is to create a shareable repository of clinical notes...

    Authors: Yaoyun Zhang, Firat Tiryaki, Min Jiang and Hua Xu
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):77
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  24. Numbers and numerical concepts appear frequently in free text clinical notes from electronic health records. Knowledge of the frequent lexical variations of these numerical concepts, and their accurate identif...

    Authors: David A. Hanauer, Qiaozhu Mei, V. G. Vinod Vydiswaran, Karandeep Singh, Zach Landis-Lewis and Chunhua Weng
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):75
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  25. Clinical entity recognition as a fundamental task of clinical text processing has been attracted a great deal of attention during the last decade. However, most studies focus on clinical text in English rather...

    Authors: Buzhou Tang, Xiaolong Wang, Jun Yan and Qingcai Chen
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):74
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  26. Osteoporosis has become an important public health issue. Most of the population, particularly elderly people, are at some degree of risk of osteoporosis-related fractures. Accurate identification and surveill...

    Authors: Yanshan Wang, Saeed Mehrabi, Sunghwan Sohn, Elizabeth J. Atkinson, Shreyasee Amin and Hongfang Liu
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):73
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  27. The amount of patient-related information within clinical information systems accumulates over time, especially in cases where patients suffer from chronic diseases with many hospitalizations and consultations...

    Authors: Markus Kreuzthaler, Bastian Pfeifer, Jose Antonio Vera Ramos, Diether Kramer, Victor Grogger, Sylvia Bredenfeldt, Markus Pedevilla, Peter Krisper and Stefan Schulz
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):72
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  28. Clinical text classification is an fundamental problem in medical natural language processing. Existing studies have cocnventionally focused on rules or knowledge sources-based feature engineering, but only a ...

    Authors: Liang Yao, Chengsheng Mao and Yuan Luo
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):71
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  29. A shareable repository of clinical notes is critical for advancing natural language processing (NLP) research, and therefore a goal of many NLP researchers is to create a shareable repository of clinical notes...

    Authors: Chunhua Weng, Carol Friedman, Casey A. Rommel and John F. Hurdle
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):70
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  30. The Health Information Technology for Economic and Clinical Health Act (HITECH) has greatly accelerated the adoption of electronic health records (EHRs) with the promise of better clinical decisions and patien...

    Authors: Liwei Wang, Yanshan Wang, Feichen Shen, Majid Rastegar-Mojarad and Hongfang Liu
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):69
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  31. Online health forums have become increasingly popular over the past several years. They provide members with a platform to network with peers and share information, experiential advice, and support. Among the ...

    Authors: V.G.Vinod Vydiswaran and Manoj Reddy
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):68
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  32. Disease prediction based on Electronic Health Records (EHR) has become one hot research topic in biomedical community. Existing work mainly focuses on the prediction of one target disease, and little work is p...

    Authors: Yafeng Ren, Hao Fei, Xiaohui Liang, Donghong Ji and Ming Cheng
    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):51
    Content type: Research Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  33. While doctors should analyze a large amount of electronic medical record (EMR) data to conduct clinical research, the analyzing process requires information technology (IT) skills, which is difficult for most ...

    Authors: Tong Ruan, Yueqi Huang, Xuli Liu, Yuhang Xia and Ju Gao
    Citation: BMC Medical Informatics and Decision Making 2019 19:82
    Content type: Research article Published on:

  34. Following publication of the original article [1], the authors reported that one of the authors’ names is spelled incorrectly.

    Authors: Gaëtan Texier, Rodrigue S. Allodji, Loty Diop, Jean-Baptiste Meynard, Liliane Pellegrin and Hervé Chaudet
    Citation: BMC Medical Informatics and Decision Making 2019 19:81
    Content type: Correction Published on:

    The original article was published in BMC Medical Informatics and Decision Making 2019 19:38

  35. 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 Published on:

  36. Digital health interventions can fill gaps in mental healthcare provision. However, autonomous e-mental health (AEMH) systems also present challenges for effective risk management. To balance autonomy and safe...

    Authors: Myrthe L. Tielman, Mark A. Neerincx, Claudia Pagliari, Albert Rizzo and Willem-Paul Brinkman
    Citation: BMC Medical Informatics and Decision Making 2019 19:47
    Content type: Research article Published on:

  37. Coronary artery disease (CAD), a leading cause of mortality, affects patient health-related quality of life (HRQoL). Elective percutaneous coronary interventions (ePCIs) are usually performed to improve HRQoL ...

    Authors: Rabah M. Al abdi, Hussam Alshraideh, Heba H. Hijazi, Mohamad Jarrah and Mohammad S. Alyahya
    Citation: BMC Medical Informatics and Decision Making 2019 19:46
    Content type: Research article Published on:

  38. 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 Published on:

  39. 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 Published on:

  40. Social isolation is an important social determinant that impacts health outcomes and mortality among patients. The National Academy of Medicine recently recommended that social isolation be documented in elect...

    Authors: Vivienne J Zhu, Leslie A Lenert, Brian E Bunnell, Jihad S Obeid, Melanie Jefferson and Chanita Hughes Halbert
    Citation: BMC Medical Informatics and Decision Making 2019 19:43
    Content type: Research article Published on:

    The Correction to this article has been published in BMC Medical Informatics and Decision Making 2019 19:89

  41. 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 Published on:

  43. Mobile health is a fast-developing field. The use of mobile health applications by healthcare professionals (HCPs) globally has increased considerably. While several studies in high income countries have inves...

    Authors: Siti Kabanda and Hanna-Andrea Rother
    Citation: BMC Medical Informatics and Decision Making 2019 19:40
    Content type: Research article Published on:

  44. Efficient planning of hospital bed usage is a necessary condition to minimize the hospital costs. In the presented work we deal with the problem of occupancy forecasting in the scale of several months, with a ...

    Authors: Ekaterina Kutafina, Istvan Bechtold, Klaus Kabino and Stephan M. Jonas
    Citation: BMC Medical Informatics and Decision Making 2019 19:39
    Content type: Research article Published on:

  45. When outbreak detection algorithms (ODAs) are considered individually, the task of outbreak detection can be seen as a classification problem and the ODA as a sensor providing a binary decision (outbreak yes o...

    Authors: Gaëtan Texier, Rodrigue S. Allodji, Loty Diop, Jean-Baptiste Meynard, Liliane Pellegrin and Hervé Chaudet
    Citation: BMC Medical Informatics and Decision Making 2019 19:38
    Content type: Research article Published on:

    The Correction to this article has been published in BMC Medical Informatics and Decision Making 2019 19:81

  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 Published on:

  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:

  48. Information about effects of treatments based on unsystematic reviews of research evidence may be misleading. However, finding trustworthy information about the effects of treatments based on systematic review...

    Authors: Andrew D. Oxman and Elizabeth J. Paulsen
    Citation: BMC Medical Informatics and Decision Making 2019 19:35
    Content type: Research article Published on:

  49. Cloud based health platforms (CBHP) have tremendous capacity to meet patient’s health needs. The benefits inherent in CBHP position it to be relevant for efficient healthcare delivery. Nonetheless, studies hav...

    Authors: Patience E. Idoga, Mehmet Toycan, Halil Nadiri and Erbuğ Çelebi
    Citation: BMC Medical Informatics and Decision Making 2019 19:34
    Content type: Research article Published on:

  50. 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 Published on:
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BMC Medical Informatics and Decision Making

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