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  1. Kidney transplant outcomes are broadly associated with transplant recipients’ capacity in following a complex and continuous self-management regimen. Health information technology has the potential to empower ...

    Authors: Saeid Eslami, Farnaz Khoshrounejad, Reza Golmakani, Zhila Taherzadeh, Fariba Tohidinezhad, Sayyed Mostafa Mostafavi and Raheleh Ganjali

    Citation: BMC Medical Informatics and Decision Making 2021 21:2

    Content type: Review

    Published on:

  2. Intrauterine Insemination (IUI) outcome prediction is a challenging issue which the assisted reproductive technology (ART) practitioners are dealing with. Predicting the success or failure of IUI based on the ...

    Authors: Sima Ranjbari, Toktam Khatibi, Ahmad Vosough Dizaji, Hesamoddin Sajadi, Mehdi Totonchi and Firouzeh Ghaffari

    Citation: BMC Medical Informatics and Decision Making 2021 21:1

    Content type: Research article

    Published on:

  3. Electronic health records (EHRs) offer various advantages for healthcare delivery, especially for chronic and complex diseases such as psoriasis. However, both patients’ and physicians’ acceptability is requir...

    Authors: Toni Maria Klein, Matthias Augustin, Natalia Kirsten and Marina Otten

    Citation: BMC Medical Informatics and Decision Making 2020 20:344

    Content type: Research article

    Published on:

  4. Electrocardiogram (ECG) signal, an important indicator for heart problems, is commonly corrupted by a low-frequency baseline wander (BW) artifact, which may cause interpretation difficulty or inaccurate analys...

    Authors: Chao-Chen Chen and Fuchiang Rich Tsui

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):343

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 11

  5. The 2020 International Conference on Intelligent Biology and Medicine (ICIBM 2020) provided a multidisciplinary forum for computational scientists and experimental biologists to share recent advances on all as...

    Authors: Li Shen, Xinghua Shi, Zhongming Zhao and Kai Wang

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):342

    Content type: Introduction

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 11

  6. Age and time information stored within the histories of clinical notes can provide valuable insights for assessing a patient’s disease risk, understanding disease progression, and studying therapeutic outcomes...

    Authors: Judy Hong, Anahita Davoudi, Shun Yu and Danielle L. Mowery

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):338

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 11

  7. Natural language processing (NLP) tools can facilitate the extraction of biomedical concepts from unstructured free texts, such as research articles or clinical notes. The NLP software tools CLAMP, cTAKES, and...

    Authors: Jacqueline Peng, Mengge Zhao, James Havrilla, Cong Liu, Chunhua Weng, Whitney Guthrie, Robert Schultz, Kai Wang and Yunyun Zhou

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):322

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 11

  8. When an Out-of-Hospital Cardiac Arrest (OHCA) incident is reported to emergency services, the 911 agent dispatches Emergency Medical Services to the location and activates responder network system (RNS), if th...

    Authors: Gaurav Rao, Salimur Choudhury, Pawan Lingras, David Savage and Vijay Mago

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):313

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 11

  9. The availability of massive amount of data enables the possibility of clinical predictive tasks. Deep learning methods have achieved promising performance on the tasks. However, most existing methods suffer fr...

    Authors: Sundreen Asad Kamal, Changchang Yin, Buyue Qian and Ping Zhang

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):307

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 11

  10. The collection and examination of social media has become a useful mechanism for studying the mental activity and behavior tendencies of users. Through the analysis of a collected set of Twitter data, a model ...

    Authors: Joseph Tassone, Peizhi Yan, Mackenzie Simpson, Chetan Mendhe, Vijay Mago and Salimur Choudhury

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):304

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 11

  11. Diabetes mellitus is a prevalent metabolic disease characterized by chronic hyperglycemia. The avalanche of healthcare data is accelerating precision and personalized medicine. Artificial intelligence and algo...

    Authors: Jiancheng Ye, Liang Yao, Jiahong Shen, Rethavathi Janarthanam and Yuan Luo

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):295

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 11

  12. Over 70% of Americans regularly experience stress. Chronic stress results in cancer, cardiovascular disease, depression, and diabetes, and thus is deeply detrimental to physiological health and psychological w...

    Authors: Russell Li and Zhandong Liu

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):285

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 11

  13. Sudden death in epilepsy (SUDEP) is a rare disease in US, however, they account for 8–17% of deaths in people with epilepsy. This disease involves complicated physiological patterns and it is still not clear w...

    Authors: Carroll Vance, Yejin Kim, Guoqiang Zhang, Samden Lhatoo, Shiqiang Tao, Licong Cui, Xiaojin Li and Xiaoqian Jiang

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 12):330

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 12

  14. Convolutional neural network (CNN) has achieved state-of-art performance in many electroencephalogram (EEG) related studies. However, the application of CNN in prediction of risk factors for sudden unexpected ...

    Authors: Cong Zhu, Yejin Kim, Xiaoqian Jiang, Samden Lhatoo, Hampson Jaison and Guo-Qiang Zhang

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 12):329

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 12

  15. Applying machine learning to healthcare sheds light on evidence-based decision making and has shown promises to improve healthcare by combining clinical knowledge and biomedical data. However, medicine and dat...

    Authors: Yejin Kim, Xiaoqian Jiang, Samden D. Lhatoo, Guo-Qiang Zhang, Shiqiang Tao, Licong Cui, Xiaojin Li, Robert D. Jolly III, Luyao Chen, Michael Phan, Cung Ha, Marijane Detranaltes and Jiajie Zhang

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 12):328

    Content type: Introduction

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 12

  16. Sudden unexpected death in epilepsy (SUDEP) is a leading cause of premature death in patients with epilepsy. If timely assessment of SUDEP risk can be made, early interventions for optimized treatments might b...

    Authors: Bishal Lamichhane, Yejin Kim, Santiago Segarra, Guoqiang Zhang, Samden Lhatoo, Jaison Hampson and Xiaoqian Jiang

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 12):327

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 12

  17. Sudden Unexpected Death in Epilepsy (SUDEP) has increased in awareness considerably over the last two decades and is acknowledged as a serious problem in epilepsy. However, the scientific community remains unc...

    Authors: Juan C. Mier, Yejin Kim, Xiaoqian Jiang, Guo-Qiang Zhang and Samden Lhatoo

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 12):326

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 12

  18. The current COVID-19 pandemic has led to a surge of research activity. While this research provides important insights, the multitude of studies results in an increasing fragmentation of information. To ensure...

    Authors: Julian Sass, Alexander Bartschke, Moritz Lehne, Andrea Essenwanger, Eugenia Rinaldi, Stefanie Rudolph, Kai U. Heitmann, Jörg J. Vehreschild, Christof von Kalle and Sylvia Thun

    Citation: BMC Medical Informatics and Decision Making 2020 20:341

    Content type: Technical advance

    Published on:

  19. Effective planning for disease prevention and control requires accurate, adequately-analysed, interpreted and communicated data. In recent years, efforts have been put in strengthening health management inform...

    Authors: Susan F. Rumisha, Emanuel P. Lyimo, Irene R. Mremi, Patrick K. Tungu, Victor S. Mwingira, Doris Mbata, Sia E. Malekia, Catherine Joachim and Leonard E. G. Mboera

    Citation: BMC Medical Informatics and Decision Making 2020 20:340

    Content type: Research article

    Published on:

  20. Routine Health Information Systems (RHIS) of low-income countries function below the globally expected standard, characterised by the production and use of poor-quality data, or the non-use of good quality dat...

    Authors: Georges Nguefack-Tsague, Brian Bongwong Tamfon, Ismael Ngnie-Teta, Marie Nicole Ngoufack, Basile Keugoung, Serge Marcial Bataliack and Chanceline Bilounga Ndongo

    Citation: BMC Medical Informatics and Decision Making 2020 20:339

    Content type: Research article

    Published on:

  21. Laboratory indicator test results in electronic health records have been applied to many clinical big data analysis. However, it is quite common that the same laboratory examination item (i.e., lab indicator) ...

    Authors: Ming Liang, ZhiXing Zhang, JiaYing Zhang, Tong Ruan, Qi Ye and Ping He

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):331

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 14

  22. Pneumothorax (PTX) may cause a life-threatening medical emergency with cardio-respiratory collapse that requires immediate intervention and rapid treatment. The screening and diagnosis of pneumothorax usually ...

    Authors: Qingfeng Wang, Qiyu Liu, Guoting Luo, Zhiqin Liu, Jun Huang, Yuwei Zhou, Ying Zhou, Weiyun Xu and Jie-Zhi Cheng

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):317

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 14

  23. A various number of imaging modalities are available (e.g., magnetic resonance, x-ray, ultrasound, and biopsy) where each modality can reveal different structural aspects of tissues. However, the analysis of h...

    Authors: Sadiq Alinsaif and Jochen Lang

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):312

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 14

  24. Ontologies are widely used throughout the biomedical domain. These ontologies formally represent the classes and relations assumed to exist within a domain. As scientific domains are deeply interlinked, so too...

    Authors: Luke T. Slater, Georgios V. Gkoutos and Robert Hoehndorf

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):311

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 10

  25. Automated summarization of scientific literature and patient records is essential for enhancing clinical decision-making and facilitating precision medicine. Most existing summarization methods are based on si...

    Authors: Eva K. Lee and Karan Uppal

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):306

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 14

  26. Ontologies house various kinds of domain knowledge in formal structures, primarily in the form of concepts and the associative relationships between them. Ontologies have become integral components of many hea...

    Authors: Ling Zheng, Yan Chen, Hua Min, P. Lloyd Hildebrand, Hao Liu, Michael Halper, James Geller, Sherri de Coronado and Yehoshua Perl

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):305

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 10

  27. It is significant to model clinical activities for process mining, which assists in improving medical service quality. However, current process mining studies in healthcare pay more attention to the control fl...

    Authors: Haifeng Xu, Jianfei Pang, Xi Yang, Jinghui Yu, Xuemeng Li and Dongsheng Zhao

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):303

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 14

  28. Increased chloride in the context of intravenous fluid chloride load and serum chloride levels (hyperchloremia) have previously been associated with increased morbidity and mortality in select subpopulations o...

    Authors: Pete Yeh, Yiheng Pan, L. Nelson Sanchez-Pinto and Yuan Luo

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):302

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 14

  29. Biological and biomedical ontologies and terminologies are used to organize and store various domain-specific knowledge to provide standardization of terminology usage and to improve interoperability. The grow...

    Authors: Ankur Agrawal and Licong Cui

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):301

    Content type: Introduction

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 10

  30. The breathing disorder obstructive sleep apnea syndrome (OSAS) only occurs while asleep. While polysomnography (PSG) represents the premiere standard for diagnosing OSAS, it is quite costly, complicated to use...

    Authors: Bin Ma, Zhaolong Wu, Shengyu Li, Ryan Benton, Dongqi Li, Yulong Huang, Mohan Vamsi Kasukurthi, Jingwei Lin, Glen M. Borchert, Shaobo Tan, Gang Li, Meihong Yang and Jingshan Huang

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):298

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 14

  31. Medical image data, like most patient information, have a strong requirement for privacy and confidentiality. This makes transmitting medical image data, within an open network, problematic, due to the aforeme...

    Authors: Jian Li, Zelin Zhang, Shengyu Li, Ryan Benton, Yulong Huang, Mohan Vamsi Kasukurthi, Dongqi Li, Jingwei Lin, Glen M. Borchert, Shaobo Tan, Gang Li, Bin Ma, Meihong Yang and Jingshan Huang

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):297

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 14

  32. Summarization networks are compact summaries of ontologies. The “Big Picture” view offered by summarization networks enables to identify sets of concepts that are more likely to have errors than control concep...

    Authors: Ling Zheng, Hua Min, Yan Chen, Vipina Keloth, James Geller, Yehoshua Perl and George Hripcsak

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):296

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 10

  33. The increasing adoption of ontologies in biomedical research and the growing number of ontologies available have made it necessary to assure the quality of these resources. Most of the well-established ontolog...

    Authors: Francisco Abad-Navarro, Manuel Quesada-Martínez, Astrid Duque-Ramos and Jesualdo Tomás Fernández-Breis

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):284

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 10

  34. Patients benefit from access to their medical records. However, clinical notes and letters are often difficult to comprehend for most lay people. Therefore, functionality was implemented in the patient portal ...

    Authors: Hugo J. T. van Mens, Mirte M. van Eysden, Remko Nienhuis, Johannes J. M. van Delden, Nicolette F. de Keizer and Ronald Cornet

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):278

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 10

  35. The National Cancer Institute (NCI) Thesaurus provides reference terminology for NCI and other systems. Previously, we proposed a hybrid prototype utilizing lexical features and role definitions of concepts in...

    Authors: Fengbo Zheng, Rashmie Abeysinghe, Nicholas Sioutos, Lori Whiteman, Lyubov Remennik and Licong Cui

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):273

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 10

  36. While enrichment of terminologies can be achieved in different ways, filling gaps in the IS-A hierarchy backbone of a terminology appears especially promising. To avoid difficult manual inspection, we started ...

    Authors: Vipina K. Keloth, James Geller, Yan Chen and Julia Xu

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):272

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 10

  37. The Kentucky Cancer Registry (KCR) is a central cancer registry for the state of Kentucky that receives data about incident cancer cases from all healthcare facilities in the state within 6 months of diagnosis...

    Authors: Shiqiang Tao, Ningzhou Zeng, Isaac Hands, Joseph Hurt-Mueller, Eric B. Durbin, Licong Cui and Guo-Qiang Zhang

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):271

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 10

  38. Dyadic-based social networks analyses have been effective in a variety of behavioral- and health-related research areas. We introduce an ontology-driven approach towards social network analysis through encodin...

    Authors: Muhammad Amith, Kayo Fujimoto, Rebecca Mauldin and Cui Tao

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):269

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 10

  39. Different from adult clinical stage I (CS1) testicular cancer, surveillance has been recommended for CS1 pediatric testicular cancer. However, among high-risk children, more than 50% suffer a relapse and progr...

    Authors: Yun-lin Ye, Zhuang-fei Chen, Jun Bian, Hai-tao Liang and Zi-ke Qin

    Citation: BMC Medical Informatics and Decision Making 2020 20:337

    Content type: Research article

    Published on:

  40. The study aimed to introduce a machine learning model that predicts in-hospital mortality in patients on mechanical ventilation (MV) following moderate to severe traumatic brain injury (TBI).

    Authors: Ahmad Abujaber, Adam Fadlalla, Diala Gammoh, Husham Abdelrahman, Monira Mollazehi and Ayman El-Menyar

    Citation: BMC Medical Informatics and Decision Making 2020 20:336

    Content type: Research article

    Published on:

  41. Acute myocardial infarction (AMI) is a serious cardiovascular disease, followed by a high readmission rate within 30-days of discharge. Accurate prediction of AMI readmission is a crucial way to identify the h...

    Authors: Zhen Zhang, Hang Qiu, Weihao Li and Yucheng Chen

    Citation: BMC Medical Informatics and Decision Making 2020 20:335

    Content type: Research article

    Published on:

  42. Hormone therapy is one option for some types of prostate cancer. Shared decision making (SDM) is important in the decision making process, but SDM between prostate cancer patients receiving hormone therapy and...

    Authors: Kazuhiro Nakayama, Wakako Osaka, Nobuaki Matsubara, Tsutomu Takeuchi, Mayumi Toyoda, Noriyuki Ohtake and Hiroji Uemura

    Citation: BMC Medical Informatics and Decision Making 2020 20:334

    Content type: Research article

    Published on:

  43. In this introduction, we first summarize the Fourth International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA 2019) held on October 26, 2019 in conjunction with the 18th International Semant...

    Authors: Zhe He, Cui Tao, Jiang Bian and Rui Zhang

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):315

    Content type: Introduction

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 4

  44. Knowledge is often produced from data generated in scientific investigations. An ever-growing number of scientific studies in several domains result into a massive amount of data, from which obtaining new know...

    Authors: Anderson Rossanez, Julio Cesar dos Reis, Ricardo da Silva Torres and Hélène de Ribaupierre

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):314

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 4

  45. To reduce cancer mortality and improve cancer outcomes, it is critical to understand the various cancer risk factors (RFs) across different domains (e.g., genetic, environmental, and behavioral risk factors) a...

    Authors: Hansi Zhang, Yi Guo, Mattia Prosperi and Jiang Bian

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):292

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 4

  46. Semantic web technology has been applied widely in the biomedical informatics field. Large numbers of biomedical datasets are available online in the resource description framework (RDF) format. Semantic relat...

    Authors: Li Zhang, Jiamei Hu, Qianzhi Xu, Fang Li, Guozheng Rao and Cui Tao

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):283

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 4

  47. Previously, we introduced our Patient Health Information Dialogue Ontology (PHIDO) that manages the dialogue and contextual information of the session between an agent and a health consumer. In this study, we ...

    Authors: Muhammad Amith, Rebecca Z. Lin, Licong Cui, Dennis Wang, Anna Zhu, Grace Xiong, Hua Xu, Kirk Roberts and Cui Tao

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):259

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 4

  48. Emotions after surviving cancer can be complicated. The survivors may have gained new strength to continue life, but some of them may begin to deal with complicated feelings and emotional stress due to trauma ...

    Authors: Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He and Xia Hu

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):254

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 4

  49. Leveraging graphs for machine learning tasks can result in more expressive power as extra information is added to the data by explicitly encoding relations between entities. Knowledge graphs are multi-relation...

    Authors: Gilles Vandewiele, Bram Steenwinckel, Filip De Turck and Femke Ongenae

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):191

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 4

  50. Treatment effect prediction (TEP) plays an important role in disease management by ensuring that the expected clinical outcomes are obtained after performing specialized and sophisticated treatments on patient...

    Authors: Jiebin Chu, Wei Dong, Jinliang Wang, Kunlun He and Zhengxing Huang

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):139

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 4

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