Articles

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

EXTraction of EMR numerical data: an efficient and generalizable tool to EXTEND clinical research

Electronic medical records (EMR) contain numerical data important for clinical outcomes research, such as vital signs and cardiac ejection fractions (EF), which tend to be embedded in narrative clinical notes....

Authors: Tianrun Cai, Luwan Zhang, Nicole Yang, Kanako K. Kumamaru, Frank J. Rybicki, Tianxi Cai and Katherine P. Liao

Frequency of ubiquitous connectivity and associated factors among Mexican adolescents

There is limited information in Mexico - a middle-income country and a digital adopter with an important demographic bonus - regarding the potential use of technology and connectivity in health promotion among...

Authors: Arturo Aguilar-Ye, Hortensia Reyes-Morales, Lourdes Campero and Nicéforo Garnelo-Bibiano

Quality analysis of smart phone sleep apps in China: can apps be used to conveniently screen for obstructive sleep apnea at home?

Obstructive sleep apnea (OSA) is a sleep disorder with a high prevalence in China. Standard diagnosis of OSA requires polysomnography (PSG). Currently, smart phone applications (apps) are widely used as an imp...

Authors: Zhao-feng Xu, Xin Luo, Jianbo Shi and Yinyan Lai

Post-acute care referral in United States of America: a multiregional study of factors associated with referral destination in a cohort of patients with coronary artery bypass graft or valve replacement

The use of post-acute care (PAC) for cardiovascular conditions is highly variable across geographical regions. Although PAC benefits include lower readmission rates, better clinical outcomes, and lower mortali...

Authors: Ineen Sultana, Madhav Erraguntla, Hye-Chung Kum, Dursun Delen and Mark Lawley

Staff expectations for the implementation of an electronic health record system: a qualitative study using normalisation process theory

Global evidence suggests a range of benefits for introducing electronic health record (EHR) systems to improve patient care. However, implementing EHR within healthcare organisations is complex and, in the Uni...

Authors: Carolyn McCrorie, Jonathan Benn, Owen Ashby Johnson and Arabella Scantlebury

Application of machine learning methodology to assess the performance of DIABETIMSS program for patients with type 2 diabetes in family medicine clinics in Mexico

The study aimed to assess the performance of a multidisciplinary-team diabetes care program called DIABETIMSS on glycemic control of type 2 diabetes (T2D) patients, by using available observational patient dat...

Authors: Yue You, Svetlana V. Doubova, Diana Pinto-Masis, Ricardo Pérez-Cuevas, Víctor Hugo Borja-Aburto and Alan Hubbard

Knowledge, attitude, and use of mHealth technology among students in Ghana: A university-based survey

Interest in mHealth interventions, defined as the use of mobile phones to access healthcare is increasingly becoming popular globally. Given its technology-based applications, university students may be key cl...

Authors: Prince Peprah, Emmanuel Mawuli Abalo, Williams Agyemang-Duah, Razak M Gyasi, Okwei Reforce, Julius Nyonyo, Godfred Amankwaa, Jones Amoako and Paulinus Kaaratoore

Mobile phone apps for clinical decision support in pregnancy: a scoping review

The use of digital technology in healthcare has been found to be useful for data collection, provision of health information and communications. Despite increasing use of medical mobile phone applications (app...

Authors: Jenny Carter, Jane Sandall, Andrew H. Shennan and Rachel M. Tribe

How should electronic health records be designed? A cross-sectional study in patients with psoriasis

Electronic health records (EHRs) are promising tools for routine care. These applications might not only enhance the interaction between patient and physician but also support therapy management. This is cruci...

Authors: Toni Maria Klein, Matthias Augustin and Marina Otten

Validating surgical procedure codes for inflammatory bowel disease in the Swedish National Patient Register

About 50% of patients with Crohn’s disease (CD) and about 20% of those with ulcerative colitis (UC) undergo surgery at some point during the course of the disease. The diagnostic validity of the Swedish Nation...

Authors: Anders Forss, Pär Myrelid, Ola Olén, Åsa H. Everhov, Caroline Nordenvall, Jonas Halfvarson and Jonas F. Ludvigsson

Merits, features, and desiderata to be considered when developing electronic health records with embedded clinical decision support systems in Palestinian hospitals: a consensus study

Electronic health records (EHRs) with embedded clinical decision support systems (CDSSs) have the potential to improve healthcare delivery. This study was conducted to explore merits, features, and desiderata ...

Authors: Ramzi Shawahna

Establishing spatially-enabled health registry systems using implicit spatial data pools: case study – Uganda

Spatial epidemiological analyses primarily depend on spatially-indexed medical records. Some countries have devised ways of capturing patient-specific spatial details using ZIP codes, postcodes or personal num...

Authors: Augustus Aturinde, Nakasi Rose, Mahdi Farnaghi, Gilbert Maiga, Petter Pilesjö and Ali Mansourian

Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma

Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. Recently, deep learning models...

Authors: Rawan AlSaad, Qutaibah Malluhi, Ibrahim Janahi and Sabri Boughorbel

Deep learning for pollen allergy surveillance from twitter in Australia

The paper introduces a deep learning-based approach for real-time detection and insights generation about one of the most prevalent chronic conditions in Australia - Pollen allergy. The popular social media pl...

Authors: Jia Rong, Sandra Michalska, Sudha Subramani, Jiahua Du and Hua Wang

Smart pumps improve medication safety but increase alert burden in neonatal care

Smart pumps have been widely adopted but there is limited evidence to understand and support their use in pediatric populations. Our objective was to assess whether smart pumps are effective at reducing medica...

Authors: Kristin R. Melton, Kristen Timmons, Kathleen E. Walsh, Jareen K. Meinzen-Derr and Eric Kirkendall

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

The hypochromic microcytic anemia (HMA) commonly found in Thailand are iron deficiency anemia (IDA) and thalassemia trait (TT). Accurate discrimination between IDA and TT is an important issue and better metho...

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

A data-driven approach to predicting diabetes and cardiovascular disease with machine learning

Diabetes and cardiovascular disease are two of the main causes of death in the United States. Identifying and predicting these diseases in patients is the first step towards stopping their progression. We eval...

Authors: An Dinh, Stacey Miertschin, Amber Young and Somya D. Mohanty

A machine-learning approach to predict postprandial hypoglycemia

For an effective artificial pancreas (AP) system and an improved therapeutic intervention with continuous glucose monitoring (CGM), predicting the occurrence of hypoglycemia accurately is very important. While...

Authors: Wonju Seo, You-Bin Lee, Seunghyun Lee, Sang-Man Jin and Sung-Min Park