Articles

Recent advances in Swedish and Spanish medical entity recognition in clinical texts using deep neural approaches

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

Does a Mobile app improve patients’ knowledge of stroke risk factors and health-related quality of life in patients with stroke? A randomized controlled trial

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

Comparing different supervised machine learning algorithms for disease prediction

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

Selection process for botulinum toxin injections in patients with chronic-stage hemiplegic stroke: a qualitative study

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

Automated segmentation of cardiomyocyte Z-disks from high-throughput scanning electron microscopy data

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

Expression alteration of microRNAs in Nucleus Accumbens is associated with chronic stress and antidepressant treatment in rats

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

Inter/intra-frame constrained vascular segmentation in X-ray angiographic image sequence

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

MultiSourcDSim: an integrated approach for exploring disease similarity

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

EEG-based image classification via a region-level stacked bi-directional deep learning framework

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

Incorporating medical code descriptions for diagnosis prediction in healthcare

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

Statistical and spectral analysis of ECG signal towards achieving non-invasive blood glucose monitoring

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

Fast read alignment with incorporation of known genomic variants

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

Heterogeneous information network based clustering for precision traditional Chinese medicine

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

Evaluating global and local sequence alignment methods for comparing patient medical records

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

Towards early detection of adverse drug reactions: combining pre-clinical drug structures and post-market safety reports

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

Promoting healthy teenage behaviour across three European countries through the use of a novel smartphone technology platform, PEGASO fit for future: study protocol of a quasi-experimental, controlled, multi-Centre trial

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…

Representation learning for clinical time series prediction tasks in electronic health records

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

A temporal visualization of chronic obstructive pulmonary disease progression using deep learning and unstructured clinical notes

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

Implementation of machine learning algorithms to create diabetic patient re-admission profiles

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

Biometric handwriting analysis to support Parkinson’s Disease assessment and grading

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

An adaptive term proximity based rocchio’s model for clinical decision support retrieval

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

A comparison between two semantic deep learning frameworks for the autosomal dominant polycystic kidney disease segmentation based on magnetic resonance images

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

A low-cost vision system based on the analysis of motor features for recognition and severity rating of Parkinson’s Disease

Assessment and rating of Parkinson’s Disease (PD) are commonly based on the medical observation of several clinical manifestations, including the analysis of motor activities. In particular, medical specialist...

Authors: Domenico Buongiorno, Ilaria Bortone, Giacomo Donato Cascarano, Gianpaolo Francesco Trotta, Antonio Brunetti and Vitoantonio Bevilacqua

Using machine learning models to improve stroke risk level classification methods of China national stroke screening

With the character of high incidence, high prevalence and high mortality, stroke has brought a heavy burden to families and society in China. In 2009, the Ministry of Health of China launched the China nationa...

Authors: Xuemeng Li, Di Bian, Jinghui Yu, Mei Li and Dongsheng Zhao

Representation learning in intraoperative vital signs for heart failure risk prediction

The probability of heart failure during the perioperative period is 2% on average and it is as high as 17% when accompanied by cardiovascular diseases in China. It has been the most significant cause of postop...

Authors: Yuwen Chen and Baolian Qi

Improving reference prioritisation with PICO recognition

Machine learning can assist with multiple tasks during systematic reviews to facilitate the rapid retrieval of relevant references during screening and to identify and extract information relevant to the study...

Authors: Austin J. Brockmeier, Meizhi Ju, Piotr Przybyła and Sophia Ananiadou

Combining entity co-occurrence with specialized word embeddings to measure entity relation in Alzheimer’s disease

Extracting useful information from biomedical literature plays an important role in the development of modern medicine. In natural language processing, there have been rigorous attempts to find meaningful rela...

Authors: Go Eun Heo, Qing Xie, Min Song and Jeong-Hoon Lee

Natural language processing for populating lung cancer clinical research data

Lung cancer is the second most common cancer for men and women; the wide adoption of electronic health records (EHRs) offers a potential to accelerate cohort-related epidemiological studies using informatics a...

Authors: Liwei Wang, Lei Luo, Yanshan Wang, Jason Wampfler, Ping Yang and Hongfang Liu

Improving rare disease classification using imperfect knowledge graph

Accurately recognizing rare diseases based on symptom description is an important task in patient triage, early risk stratification, and target therapies. However, due to the very nature of rare diseases, the ...

Authors: Xuedong Li, Yue Wang, Dongwu Wang, Walter Yuan, Dezhong Peng and Qiaozhu Mei

TestIME: an application for evaluating the efficiency of Chinese input method engines in electronic medical record entry task

With the wide application of Electronic Medical Record (EMR) systems, it has become a daily work for doctors using keyboards to input clinical information into the EMR system. Chinese Input Method Engine (IME)...

Authors: Feihong Yang, Haihong Guo and Jiao Li

Applying a deep learning-based sequence labeling approach to detect attributes of medical concepts in clinical text

To detect attributes of medical concepts in clinical text, a traditional method often consists of two steps: named entity recognition of attributes and then relation classification between medical concepts and...

Authors: Jun Xu, Zhiheng Li, Qiang Wei, Yonghui Wu, Yang Xiang, Hee-Jin Lee, Yaoyun Zhang, Stephen Wu and Hua Xu

An attention-based deep learning model for clinical named entity recognition of Chinese electronic medical records

Clinical named entity recognition (CNER) is important for medical information mining and establishment of high-quality knowledge map. Due to the different text features from natural language and a large number...

Authors: Luqi Li, Jie Zhao, Li Hou, Yunkai Zhai, Jinming Shi and Fangfang Cui

RCorp: a resource for chemical disease semantic extraction in Chinese

To robustly identify synergistic combinations of drugs, high-throughput screenings are desirable. It will be of great help to automatically identify the relations in the published papers with machine learning ...

Authors: Yueping Sun, Li Hou, Lu Qin, Yan Liu, Jiao Li and Qing Qian

Editorial: The second international workshop on health natural language processing (HealthNLP 2019)

Authors: Yanshan Wang, Hua Xu and Ozlem Uzuner

A study of deep learning methods for de-identification of clinical notes in cross-institute settings

De-identification is a critical technology to facilitate the use of unstructured clinical text while protecting patient privacy and confidentiality. The clinical natural language processing (NLP) community has...

Authors: Xi Yang, Tianchen Lyu, Qian Li, Chih-Yin Lee, Jiang Bian, William R. Hogan and Yonghui Wu

Proof-of-concept study: Homomorphically encrypted data can support real-time learning in personalized cancer medicine

The successful introduction of homomorphic encryption (HE) in clinical research holds promise for improving acceptance of data-sharing protocols, increasing sample sizes, and accelerating learning from real-wo...

Authors: Silvia Paddock, Hamed Abedtash, Jacqueline Zummo and Samuel Thomas

Deterrence approach on the compliance with electronic medical records privacy policy: the moderating role of computer monitoring

This study explored the possible antecedents that will motivate hospital employees’ compliance with privacy policy related to electronic medical records (EMR) from a deterrence perspective. Further, we also in...

Authors: Kuang-Ming Kuo, Paul C. Talley and Tain-Junn Cheng

Working with patients and the public to design an electronic health record interface: a qualitative mixed-methods study

Enabling patients to be active users of their own medical records may promote the delivery of safe, efficient care across settings. Patients are rarely involved in designing digital health record systems which...

Authors: Leigh R. Warren, Matthew Harrison, Sonal Arora and Ara Darzi

Effectiveness of a chat-bot for the adult population to quit smoking: protocol of a pragmatic clinical trial in primary care (Dejal@)

The wide scale and severity of consequences of tobacco use, benefits derived from cessation, low rates of intervention by healthcare professionals, and new opportunities stemming from novel communications tech...

Authors: J. F. Avila-Tomas, E. Olano-Espinosa, C. Minué-Lorenzo, F. J. Martinez-Suberbiola, B. Matilla-Pardo, M. E. Serrano-Serrano and E. Escortell-Mayor

Identifying undetected dementia in UK primary care patients: a retrospective case-control study comparing machine-learning and standard epidemiological approaches

Identifying dementia early in time, using real world data, is a public health challenge. As only two-thirds of people with dementia now ultimately receive a formal diagnosis in United Kingdom health systems an...

Authors: Elizabeth Ford, Philip Rooney, Seb Oliver, Richard Hoile, Peter Hurley, Sube Banerjee, Harm van Marwijk and Jackie Cassell

Standards as applied in reality: a case study on the translation of standards in eHealth evaluation practice

Application of standards is a way to increase quality in an evaluation study. However, standards are used insufficiently in eHealth evaluation, affecting the generalization of the knowledge generated.

Authors: Monika Jurkeviciute

Developing a standardised approach to the aggregation of inpatient episodes into person-based spells in all specialties and psychiatric specialties

Electronic health record (EHR) data are available for research in all UK nations and cross-nation comparative studies are becoming more common. All UK inpatient EHRs are based around episodes, but episode-base...

Authors: Sarah Rees, Ashley Akbari, Huw Collins, Sze Chim Lee, Amanda Marchant, Arfon Rees, Daniel Thayer, Ting Wang, Sophie Wood and Ann John

Effectiveness of electronic point-of-care reminders versus monthly feedback to improve adherence to 10 clinical recommendations in primary care: a cluster randomized clinical trial

Numerous studies have analyzed the effectiveness of electronic reminder interventions to improve different clinical conditions, and most have reported a small to moderate effect. Few studies, however, have ana...

Authors: Ermengol Coma, Manuel Medina, Leonardo Méndez, Eduardo Hermosilla, Manuel Iglesias, Carmen Olmos and Sebastian Calero

Latent Dirichlet Allocation in predicting clinical trial terminations

This study used natural language processing (NLP) and machine learning (ML) techniques to identify reliable patterns from within research narrative documents to distinguish studies that complete successfully, ...

Authors: Simon Geletta, Lendie Follett and Marcia Laugerman

Evaluating the implementation of a personal health record for chronic primary and secondary care: a mixed methods approach

Personal health records (PHRs) provide the opportunity for self-management support, enhancing communication between patients and caregivers, and maintaining and/or improving the quality of chronic disease mana...

Authors: Floor Sieverink, Saskia Kelders, Annemarie Braakman-Jansen and Julia van Gemert-Pijnen

Prediction of cognitive impairment via deep learning trained with multi-center neuropsychological test data

Neuropsychological tests (NPTs) are important tools for informing diagnoses of cognitive impairment (CI). However, interpreting NPTs requires specialists and is thus time-consuming. To streamline the applicati...

Authors: Min Ju Kang, Sang Yun Kim, Duk L. Na, Byeong C. Kim, Dong Won Yang, Eun-Joo Kim, Hae Ri Na, Hyun Jeong Han, Jae-Hong Lee, Jong Hun Kim, Kee Hyung Park, Kyung Won Park, Seol-Heui Han, Seong Yoon Kim, Soo Jin Yoon, Bora Yoon…

“Assessment of the social influence and facilitating conditions that support nurses’ adoption of hospital electronic information management systems (HEIMS) in Ghana using the unified theory of acceptance and use of technology (UTAUT) model”

Hospital electronic information management systems (HEIMS) are widely used in Ghana, and hence its performance must be carefully assessed. Nurses as clinical health personnel are the largest cluster of hospita...

Authors: Lu Lin Zhou, Joseph Owusu-Marfo, Henry Asante Antwi, Maxwell Opuni Antwi, Arielle Doris Tetgoum Kachie and Sabina Ampon-Wireko

A novel hybrid modeling approach for the evaluation of integrated care and economic outcome in heart failure treatment

Demographic changes, increased life expectancy and the associated rise in chronic diseases pose challenges to public health care systems. Optimized treatment methods and integrated concepts of care are potenti...

Authors: Alexander Lassnig, Theresa Rienmueller, Diether Kramer, Werner Leodolter, Christian Baumgartner and Joerg Schroettner

Correction to: ThalPred: a web-based prediction tool for discriminating thalassemia trait and iron deficiency anemia

Following publication of the original article [1], the authors reported an error in one of the authors’ names. In this Correction the incorrect and correct author name are shown. The original publication of th...

Authors: V. Laengsri, W. Shoombuatong, W. Adirojananon, C. Nantasenamat, V. Prachayasittikul and P. Nuchnoi

Correction to: Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system

Following publication of the original article [1], the authors reported that the article erroneously stated that Dr. Ancker was affiliated with the Tehran University of Medical Sciences. Dr. Ancker is not affi...

Authors: Jessica S. Ancker, Alison Edwards, Sarah Nosal, Diane Hauser, Elizabeth Mauer and Rainu Kaushal