Articles

Mobile phone usage in patients with type II diabetes and their intention to use it for self-management: a cross-sectional study in Iran

Mobile health has potential for promotion of self-management in patients with chronic diseases. This study was conducted to investigate smartphone usage in patients with type II diabetes and their intention to...

Authors: Fatemeh Rangraz Jeddi, Ehsan Nabovati, Rahele Hamidi and Reihane Sharif

Retrieving 3D medical data along fitted curved slices and their display

Computeros tomography and magnetic resonance imaging are usually offered to the clinician in the form of sequences of axial, sagittal and coronal planar cuts. Frequently this does not allow for the full inspec...

Authors: Marco Paluszny and Dany Ríos

Improving prediction performance of colon cancer prognosis based on the integration of clinical and multi-omics data

Colon cancer is common worldwide and is the leading cause of cancer-related death. Multiple levels of omics data are available due to the development of sequencing technologies. In this study, we proposed an i...

Authors: Danyang Tong, Yu Tian, Tianshu Zhou, Qiancheng Ye, Jun Li, Kefeng Ding and Jingsong Li

Predicting patient outcomes in psychiatric hospitals with routine data: a machine learning approach

A common problem in machine learning applications is availability of data at the point of decision making. The aim of the present study was to use routine data readily available at admission to predict aspects...

Authors: J. Wolff, A. Gary, D. Jung, C. Normann, K. Kaier, H. Binder, K. Domschke, A. Klimke and M. Franz

Contribution of a synchronic teleneurology program to decrease the patient number waiting for a first consultation and their waiting time in Chile

Backround

Authors: Freddy Constanzo, Paula Aracena-Sherck, Juan Pablo Hidalgo, Lorena Peña, Mery Marrugo, Jonathan Gonzalez, Gerardo Vergara and Cristóbal Alvarado

Investigating usability of mobile health applications in Bangladesh

Lack of usability can be a major barrier for the rapid adoption of mobile services. Therefore, the purpose of this paper is to investigate the usability of Mobile Health applications in Bangladesh.

Authors: Muhammad Nazrul Islam, Md. Mahboob Karim, Toki Tahmid Inan and A. K. M. Najmul Islam

A stratification method based on clustering for the minimization of data masking effect in signal detection

Data masking is an inborn defect of measures of disproportionality in adverse drug reactions (ADRs) signal detection. Many previous studies can be roughly classified into three categories: data removal, regres...

Authors: Jian-Xiang Wei, Yue Ding, Ming Li and Jun Sun

Tracking physical activity using smart phone apps: assessing the ability of a current app and systematically collecting patient recommendations for future development

Within the United Kingdom’s National Health System (NHS), patients suffering from obesity may be provided with bariatric surgery. After receiving surgery many of these patients require further support to conti...

Authors: J. Murphy, T. Uttamlal, K. A. Schmidtke, I. Vlaev, D. Taylor, M. Ahmad, S. Alsters, P. Purkayastha, S. Scholtz, R. Ramezani, A. R. Ahmed, H. Chahal, A. Darzi and A. I. F. Blakemore

Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone

Cardiovascular diseases kill approximately 17 million people globally every year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) occurs when the heart cannot pump enou...

Authors: Davide Chicco and Giuseppe Jurman

Novel methodology to measure pre-procedure antimicrobial prophylaxis: integrating text searches with structured data from the Veterans Health Administration’s electronic medical record

Antimicrobial prophylaxis is an evidence-proven strategy for reducing procedure-related infections; however, measuring this key quality metric typically requires manual review, due to the way antimicrobial pro...

Authors: Hillary J. Mull, Kelly Stolzmann, Emily Kalver, Marlena H. Shin, Marin L. Schweizer, Archana Asundi, Payal Mehta, Maggie Stanislawski and Westyn Branch-Elliman

Customization scenarios for de-identification of clinical notes

Automated machine-learning systems are able to de-identify electronic medical records, including free-text clinical notes. Use of such systems would greatly boost the amount of data available to researchers, y...

Authors: Tzvika Hartman, Michael D. Howell, Jeff Dean, Shlomo Hoory, Ronit Slyper, Itay Laish, Oren Gilon, Danny Vainstein, Greg Corrado, Katherine Chou, Ming Jack Po, Jutta Williams, Scott Ellis, Gavin Bee, Avinatan Hassidim, Rony Amira…

Design and implementation of a clinical decision support tool for primary palliative Care for Emergency Medicine (PRIM-ER)

The emergency department is a critical juncture in the trajectory of care of patients with serious, life-limiting illness. Implementation of a clinical decision support (CDS) tool automates identification of o...

Authors: Audrey Tan, Mark Durbin, Frank R. Chung, Ada L. Rubin, Allison M. Cuthel, Jordan A. McQuilkin, Aram S. Modrek, Catherine Jamin, Nicholas Gavin, Devin Mann, Jordan L. Swartz, Jonathan S. Austrian, Paul A. Testa, Jacob D. Hill and Corita R. Grudzen

A mobile app implementing the international classification of functioning, disability and health rehabilitation set

The Chinese assessment standards of the International Classification of Functioning, Disability and Health Rehabilitation Set is available now. It is coming to be used as a basic functional evaluation tool in ...

Authors: Malan Zhang, Jiani Yu, Wei Shen, Yun Zhang, Yun Xiang, Xinting Zhang, Ziling Lin and Tiebin Yan

Assessment of willingness to Tele-monitoring interventions in patients with type 2 diabetes and/or hypertension in the public primary healthcare setting

Tele-monitoring (TM) is remote monitoring of individuals via info-communication technology, enabling them and their relatives or care-providers to recognize their health status conveniently. TM will be success...

Authors: David Yang Ern Sin, Xiaoxuan Guo, Dayna Wei Wei Yong, Tian Yu Qiu, Peter Kirm Seng Moey, Muller-Riemenschneider Falk and Ngiap Chuan Tan

Usage of cloud storage facilities by medical students in a low-middle income country, Sri Lanka: a cross sectional study

Cloud storage facilities (CSF) has become popular among the internet users. There is limited data on CSF usage among university students in low middle-income countries including Sri Lanka. In this study we pre...

Authors: Samankumara Hettige, Eshani Dasanayaka and Dileepa Senajith Ediriweera

Inverse-probability weighting and multiple imputation for evaluating selection bias in the estimation of childhood obesity prevalence using data from electronic health records

Height and weight data from electronic health records are increasingly being used to estimate the prevalence of childhood obesity. Here, we aim to assess the selection bias due to missing weight and height dat...

Authors: Carmen Sayon-Orea, Conchi Moreno-Iribas, Josu Delfrade, Manuela Sanchez-Echenique, Pilar Amiano, Eva Ardanaz, Javier Gorricho, Garbiñe Basterra, Marian Nuin and Marcela Guevara

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

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