Articles

Assessing stroke severity using electronic health record data: a machine learning approach

Stroke severity is an important predictor of patient outcomes and is commonly measured with the National Institutes of Health Stroke Scale (NIHSS) scores. Because these scores are often recorded as free text i...

Authors: Emily Kogan, Kathryn Twyman, Jesse Heap, Dejan Milentijevic, Jennifer H. Lin and Mark Alberts

Exploring the usefulness of Lexis diagrams for quality improvement

Visualization is important to aid practitioners in understanding local care processes and drive quality improvement (QI). Important aspects include timely feedback and ability to plot data over time. Moreover,...

Authors: Sara Dahlin

Predicting diabetes clinical outcomes using longitudinal risk factor trajectories

The ubiquity of electronic health records (EHR) offers an opportunity to observe trajectories of laboratory results and vital signs over long periods of time. This study assessed the value of risk factor traje...

Authors: Gyorgy J. Simon, Kevin A. Peterson, M. Regina Castro, Michael S. Steinbach, Vipin Kumar and Pedro J. Caraballo

Can mobile health apps replace GPs? A scoping review of comparisons between mobile apps and GP tasks

Mobile health applications (mHealth apps) are increasingly being used to perform tasks that are conventionally performed by general practitioners (GPs), such as those involved in promoting health, preventing d...

Authors: Apichai Wattanapisit, Chin Hai Teo, Sanhapan Wattanapisit, Emylia Teoh, Wing Jun Woo and Chirk Jenn Ng

A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learning algorithms

In classification and diagnostic testing, the receiver-operator characteristic (ROC) plot and the area under the ROC curve (AUC) describe how an adjustable threshold causes changes in two types of error: false...

Authors: André M. Carrington, Paul W. Fieguth, Hammad Qazi, Andreas Holzinger, Helen H. Chen, Franz Mayr and Douglas G. Manuel

Novel prognostication of patients with spinal and pelvic chondrosarcoma using deep survival neural networks

We used the Surveillance, Epidemiology, and End Results (SEER) database to develop and validate deep survival neural network machine learning (ML) algorithms to predict survival following a spino-pelvic chondr...

Authors: Sung Mo Ryu, Sung Wook Seo and Sun-Ho Lee

Digital health Systems in Kenyan Public Hospitals: a mixed-methods survey

As healthcare facilities in Low- and Middle-Income Countries adopt digital health systems to improve hospital administration and patient care, it is important to understand the adoption process and assess the ...

Authors: Naomi Muinga, Steve Magare, Jonathan Monda, Mike English, Hamish Fraser, John Powell and Chris Paton

Development of a targeted client communication intervention to women using an electronic maternal and child health registry: a qualitative study

Targeted client communication (TCC) using text messages can inform, motivate and remind pregnant and postpartum women of timely utilization of care. The mixed results of the effectiveness of TCC interventions ...

Authors: Binyam Bogale, Kjersti Mørkrid, Brian O’Donnell, Buthaina Ghanem, Itimad Abu Ward, Khadija Abu Khader, Mervett Isbeih, Michael Frost, Mohammad Baniode, Taghreed Hijaz, Tamara Awwad, Yousef Rabah and J. Frederik Frøen

Acceptability of Internet-based interventions for problem gambling: a qualitative study of focus groups with clients and clinicians

Although Internet-based interventions (IBIs) have been around for two decades, uptake has been slow. Increasing the acceptability of IBIs among end users may increase uptake. In this study, we explored the fac...

Authors: Sherald Sanchez, Farah Jindani, Jing Shi, Mark van der Maas, Sylvia Hagopian, Robert Murray and Nigel Turner

AliClu - Temporal sequence alignment for clustering longitudinal clinical data

Patient stratification is a critical task in clinical decision making since it can allow physicians to choose treatments in a personalized way. Given the increasing availability of electronic medical records (...

Authors: Kishan Rama, Helena Canhão, Alexandra M. Carvalho and Susana Vinga

The implementation of natural language processing to extract index lesions from breast magnetic resonance imaging reports

There are often multiple lesions in breast magnetic resonance imaging (MRI) reports and radiologists usually focus on describing the index lesion that is most crucial to clinicians in determining the managemen...

Authors: Yi Liu, Qing Liu, Chao Han, Xiaodong Zhang and Xiaoying Wang

Use of natural language processing to improve predictive models for imaging utilization in children presenting to the emergency department

To examine the association between the medical imaging utilization and information related to patients’ socioeconomic, demographic and clinical factors during the patients’ ED visits; and to develop predictive...

Authors: Xingyu Zhang, M. Fernanda Bellolio, Pau Medrano-Gracia, Konrad Werys, Sheng Yang and Prashant Mahajan

DeepFHR: intelligent prediction of fetal Acidemia using fetal heart rate signals based on convolutional neural network

Fetal heart rate (FHR) monitoring is a screening tool used by obstetricians to evaluate the fetal state. Because of the complexity and non-linearity, a visual interpretation of FHR signals using common guideli...

Authors: Zhidong Zhao, Yanjun Deng, Yang Zhang, Yefei Zhang, Xiaohong Zhang and Lihuan Shao

Forecasting one-day-forward wellness conditions for community-dwelling elderly with single lead short electrocardiogram signals

The accelerated growth of elderly population is creating a heavy burden to the healthcare system in many developed countries and regions. Electrocardiogram (ECG) analysis has been recognized as effective appro...

Authors: Xiaomao Fan, Yang Zhao, Hailiang Wang and Kwok Leung Tsui

A Bayesian decision support sequential model for severity of illness predictors and intensive care admissions in pneumonia

Community-acquired pneumonia (CAP) is one of the leading causes of morbidity and mortality in the USA. Our objective was to assess the predictive value on critical illness and disposition of a sequential Bayes...

Authors: Amado Alejandro Baez, Laila Cochon and Jose Maria Nicolas

Responsible data sharing in a big data-driven translational research platform: lessons learned

To foster responsible data sharing in health research, ethical governance complementary to the EU General Data Protection Regulation is necessary. A governance framework for Big Data-driven research platforms ...

Authors: S. Kalkman, M. Mostert, N. Udo-Beauvisage, J. J. van Delden and G. J. van Thiel

Family history information extraction via deep joint learning

Family history (FH) information, including family members, side of family of family members (i.e., maternal or paternal), living status of family members, observations (diseases) of family members, etc., is ve...

Authors: Xue Shi, Dehuan Jiang, Yuanhang Huang, Xiaolong Wang, Qingcai Chen, Jun Yan and Buzhou Tang

Selected articles from the BioCreative/OHNLP challenge 2018

Authors: Sijia Liu, Yanshan Wang and Hongfang Liu

Family member information extraction via neural sequence labeling models with different tag schemes

Family history information (FHI) described in unstructured electronic health records (EHRs) is a valuable information source for patient care and scientific researches. Since FHI is usually described in the fo...

Authors: Hong-Jie Dai

Using an artificial neural network to map cancer common data elements to the biomedical research integrated domain group model in a semi-automated manner

The medical community uses a variety of data standards for both clinical and research reporting needs. ISO 11179 Common Data Elements (CDEs) represent one such standard that provides robust data point definiti...

Authors: Robinette Renner, Shengyu Li, Yulong Huang, Ada Chaeli van der Zijp-Tan, Shaobo Tan, Dongqi Li, Mohan Vamsi Kasukurthi, Ryan Benton, Glen M. Borchert, Jingshan Huang and Guoqian Jiang

Muscle fatigue detection and treatment system driven by internet of things

Internet of things is fast becoming the norm in everyday life, and integrating the Internet into medical treatment, which is increasing day by day, is of high utility to both clinical doctors and patients. Whi...

Authors: Bin Ma, Chunxiao Li, Zhaolong Wu, Yulong Huang, Ada Chaeli van der Zijp-Tan, Shaobo Tan, Dongqi Li, Ada Fong, Chandan Basetty, Glen M. Borchert, Ryan Benton, Bin Wu and Jingshan Huang

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

Improving clinical named entity recognition in Chinese using the graphical and phonetic feature

Clinical Named Entity Recognition is to find the name of diseases, body parts and other related terms from the given text. Because Chinese language is quite different with English language, the machine cannot ...

Authors: Yifei Wang, Sophia Ananiadou and Jun’ichi Tsujii

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

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

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