Articles

Machine learning to help researchers evaluate biases in clinical trials: a prospective, randomized user study

Assessing risks of bias in randomized controlled trials (RCTs) is an important but laborious task when conducting systematic reviews. RobotReviewer (RR), an open-source machine learning (ML) system, semi-autom...

Authors: Frank Soboczenski, Thomas A. Trikalinos, Joël Kuiper, Randolph G. Bias, Byron C. Wallace and Iain J. Marshall

Accessing and sharing health information for post-discharge stroke care through a national health information exchange platform - a case study

Patients and citizens need access to their health information to get a retrospective as well as a prospective view on their care and rehabilitation processes. However, patients’ health information is stored in...

Authors: Nadia Davoody, Sabine Koch, Ingvar Krakau and Maria Hägglund

Quantile-based fecal hemoglobin concentration for assessing colorectal neoplasms with 1,263,717 Taiwanese screenees

Although fecal hemoglobin concentration (f-Hb) was highly associated with the risk of colorectal neoplasms, current studies on this subject are hampered by skewedness of the data and the ordinal property of f-...

Authors: Szu-Min Peng, Han-Mo Chiu, Hsiao-Hsuan Jen, Chen-Yang Hsu, Sam Li-Sheng Chen, Sherry Yueh-Hsia Chiu, Amy Ming-Fang Yen, Jean Ching-Yuan Fann, Yi-Chia Lee and Hsiu-Hsi Chen

An open access medical knowledge base for community driven diagnostic decision support system development

While early diagnostic decision support systems were built around knowledge bases, more recent systems employ machine learning to consume large amounts of health data. We argue curated knowledge bases will rem...

Authors: Lars Müller, Rashmi Gangadharaiah, Simone C. Klein, James Perry, Greg Bernstein, David Nurkse, Dustin Wailes, Rishi Graham, Robert El-Kareh, Sanjay Mehta, Staal A. Vinterbo and Eliah Aronoff-Spencer

“OPTImAL”: an ontology for patient adherence modeling in physical activity domain

Maintaining physical fitness is a crucial component of the therapeutic process for patients with cardiovascular disease (CVD). Despite the known importance of being physically active, patient adherence to exer...

Authors: Kristina Livitckaia, Vassilis Koutkias, Evangelia Kouidi, Mark van Gils, Nikolaos Maglaveras and Ioanna Chouvarda

Using the distance between sets of hierarchical taxonomic clinical concepts to measure patient similarity

Many clinical concepts are standardized under a categorical and hierarchical taxonomy such as ICD-10, ATC, etc. These taxonomic clinical concepts provide insight into semantic meaning and similarity among clin...

Authors: Zheng Jia, Xudong Lu, Huilong Duan and Haomin Li

Taking patient involvement seriously: a critical ethical analysis of participatory approaches in data-intensive medical research

Data-intensive research in medicine and healthcare such as health-related big data research (HBDR) implies that data from clinical routine, research and patient-reported data, but also non-medical social or de...

Authors: Katharina Beier, Mark Schweda and Silke Schicktanz

Correction to: Automatically identifying social isolation from clinical narratives for patients with prostate Cancer

Following publication of the original article [1], the authors reported an error in one of the authors’ names.

Authors: Vivienne J. Zhu, Leslie A. Lenert, Brian E. Bunnell, Jihad S. Obeid, Melanie Jefferson and Chanita Hughes Halbert

Are Austrian practitioners ready to use medical apps? Results of a validation study

As part of the mobile revolution, smartphone-based applications (apps) have become almost indispensable in today’s information society. Consequently, the use of medical apps among healthcare professionals has ...

Authors: Fanni Hofer and Daniela Haluza

GatewayNet: a form of sequential rule mining

The gateway hypothesis (and particularly the prediction of developmental stages in drug abuse) has been a subject of protracted debate since the 1970s. Extensive research has gone into this subject, but has yi...

Authors: Phillip C. S. R. Kilgore, Nadejda Korneeva, Thomas C. Arnold, Marjan Trutschl and Urška Cvek

Identifying clinically important COPD sub-types using data-driven approaches in primary care population based electronic health records

COPD is a highly heterogeneous disease composed of different phenotypes with different aetiological and prognostic profiles and current classification systems do not fully capture this heterogeneity. In this s...

Authors: Maria Pikoula, Jennifer Kathleen Quint, Francis Nissen, Harry Hemingway, Liam Smeeth and Spiros Denaxas

Falls Sensei: a serious 3D exploration game to enable the detection of extrinsic home fall hazards for older adults

Falls are the main cause of death and injury for older adults in the UK. Many of these falls occur within the home as a result of extrinsic falls risk factors such as poor lighting, loose/uneven flooring, and ...

Authors: Arthur G. Money, Anita Atwal, Emily Boyce, Sophie Gaber, Susan Windeatt and Kyriakos Alexandrou

Talking about treatment benefits, harms, and what matters to patients in radiation oncology: an observational study

Shared decision making is associated with improved patient outcomes in radiation oncology. Our study aimed to capture how shared decision-making practices–namely, communicating potential harms and benefits and...

Authors: Laurie Pilote, Luc Côté, Selma Chipenda Dansokho, Émilie Brouillard, Anik M. C. Giguère, France Légaré, Roland Grad and Holly O. Witteman

Discover high-risk factor combinations using Bayesian network from cohort data of National Stoke Screening in China

In recent years, the increasing incidence and prevalence of stroke has brought a heavy economic burden on families and society in China. The Ministry of Health of the Peoples’ Republic of China initiated the n...

Authors: Xuemeng Li, Jianfei Pang, Mei Li and Dongsheng Zhao

A fine-grained Chinese word segmentation and part-of-speech tagging corpus for clinical text

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

A deep learning model incorporating part of speech and self-matching attention for named entity recognition of Chinese electronic medical records

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

A hybrid approach for named entity recognition in Chinese electronic medical record

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

Hierarchical sequence labeling for extracting BEL statements from biomedical literature

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

An approach for transgender population information extraction and summarization from clinical trial text

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

Evidential MACE prediction of acute coronary syndrome using electronic health records

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

Incorporating causal factors into reinforcement learning for dynamic treatment regimes in HIV

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

Relation path feature embedding based convolutional neural network method for drug discovery

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

Time-sensitive clinical concept embeddings learned from large electronic health records

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

Inverse reinforcement learning for intelligent mechanical ventilation and sedative dosing in intensive care units

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

Constructing a Chinese electronic medical record corpus for named entity recognition on resident admit notes

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

Attention-based deep residual learning network for entity relation extraction in Chinese EMRs

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

An approach for medical event detection in Chinese clinical notes of electronic health records

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

An ontological framework for the formalization, organization and usage of TCM-Knowledge

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

Applying deep matching networks to Chinese medical question answering: a study and a dataset

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

Discovering thematic change and evolution of utilizing social media for healthcare research

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

On building a diabetes centric knowledge base via mining the web

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

Mobile phone applications to overcome malnutrition among preschoolers: a systematic review

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

Facilitating accurate health provider directories using natural language processing

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

Extracting health-related causality from twitter messages using natural language processing

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

Developing a portable natural language processing based phenotyping system

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

Parsing clinical text using the state-of-the-art deep learning based parsers: a systematic comparison

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

Special issue of BMC medical informatics and decision making on health natural language processing

Authors: V. G. Vinod Vydiswaran, Yaoyun Zhang, Yanshan Wang and Hua Xu

Complexities, variations, and errors of numbering within clinical notes: the potential impact on information extraction and cohort-identification

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

Entity recognition in Chinese clinical text using attention-based CNN-LSTM-CRF

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

Natural language processing of radiology reports for identification of skeletal site-specific fractures

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

EHR problem list clustering for improved topic-space navigation

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

Clinical text classification with rule-based features and knowledge-guided convolutional neural networks

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

A two-site survey of medical center personnel’s willingness to share clinical data for research: implications for reproducible health NLP research

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

Discovering associations between problem list and practice setting

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

Identifying peer experts in online health forums

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

A hybrid neural network model for predicting kidney disease in hypertension patients based on electronic health records

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

QAnalysis: a question-answer driven analytic tool on knowledge graphs for leveraging electronic medical records for clinical research

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

Correction to: Using decision fusion methods to improve outbreak detection in disease surveillance

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

Predicting factors for survival of breast cancer patients using machine learning techniques

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

QL⁴MDR: a GraphQL query language for ISO 11179-based metadata repositories

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