Data Mining Techniques Utilizing Latent Class Models to Evaluate Emergency Department Revisits
ConclusionsThese findings suggest that one prospective approach to advanced risk prediction is to leverage the longitudinal nature of health care data by exploiting patients’ between state variation.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - November 19, 2019 Category: Information Technology Source Type: research

An Archetype Query Language interpreter into MongoDB: managing NoSQL standardized Electronic Health Record extracts systems
Publication date: Available online 13 November 2019Source: Journal of Biomedical InformaticsAuthor(s): Miguel Ramos, Ricardo Sánchez-de-Madariaga, Jesús Barros, Lino Carrajo, Guillermo Vázquez, Santiago Pérez, Mario Pascual, Fernando Martín-Sánchez, Adolfo Muñoz-CarreroAbstractThe fast development of today’s healthcare and the need to extract new medical knowledge from exponentially-growing volumes of standardized Electronic Health Records data, as required by studies in Precision Medicine, brings up a challenge that may probably only be addressed using NoSQL DBMSs, du...
Source: Journal of Biomedical Informatics - November 13, 2019 Category: Information Technology Source Type: research

State of the Art and a Mixed-Method Personalized Approach to Assess Patients Perceptions on Medical Record Sharing and Sensitivity
ConclusionThe findings indicate diversity in patient views on EHR sensitivity and data sharing preferences and the need for more granular and patient-centered electronic consent mechanisms to accommodate patient needs. More research is needed to validate the generalizability of the proposed methodology.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - November 13, 2019 Category: Information Technology Source Type: research

SECNLP: A Survey of Embeddings in Clinical Natural Language Processing
Publication date: Available online 8 November 2019Source: Journal of Biomedical InformaticsAuthor(s): Kalyan Katikapalli Subramanyam, Sangeetha SivanesanAbstractDistributed vector representations or embeddings map variable length text to dense fixed length vectors as well as capture prior knowledge which can transferred to downstream tasks. Even though embeddings have become de facto standard for representations in deep learning based NLP tasks in both general and clinical domains, there is no survey paper which presents a detailed review of embeddings in Clinical Natural Language Processing. In this survey paper, we discu...
Source: Journal of Biomedical Informatics - November 10, 2019 Category: Information Technology Source Type: research

Cover 1/Spine
Publication date: November 2019Source: Journal of Biomedical Informatics, Volume 99Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - November 8, 2019 Category: Information Technology Source Type: research

Cover 2: Editorial Board
Publication date: November 2019Source: Journal of Biomedical Informatics, Volume 99Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - November 8, 2019 Category: Information Technology Source Type: research

fmi-ii: Table of Contents
Publication date: November 2019Source: Journal of Biomedical Informatics, Volume 99Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - November 8, 2019 Category: Information Technology Source Type: research

fmiii: Copyright/ID Statement
Publication date: November 2019Source: Journal of Biomedical Informatics, Volume 99Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - November 8, 2019 Category: Information Technology Source Type: research

PharmActa: Personalized pharmaceutical care eHealth platform for patients and pharmacists
Publication date: Available online 2 November 2019Source: Journal of Biomedical InformaticsAuthor(s): Marios Spanakis, Stelios Sfakianakis, George Kallergis, Emmanouil G. Spanakis, Vangelis SakkalisAbstractCommunity pharmacists are critically placed in the patient care chain being an extended frontline within primary healthcare networks across Europe. They are trained to ensure safe and effective medication use, a crucial and responsible role, extending beyond the common misconception limited to just providing timely access to medicines for the population. Technology-wise, eHealth being committed to an effective, networked...
Source: Journal of Biomedical Informatics - November 4, 2019 Category: Information Technology Source Type: research

Temporal phenotyping by mining healthcare data to derive lines of therapy for cancer
Publication date: Available online 2 November 2019Source: Journal of Biomedical InformaticsAuthor(s): Weilin Meng, Wanmei Ou, Sheenu Chandwani, Xin Chen, Wynona Black, Zhaohui CaiAbstractLines of therapy (LOT) derived from real-world healthcare data not only depict real-world cancer treatment sequences, but also help define patient phenotypes along the course of disease progression and therapeutic interventions. The sequence of prescribed anticancer therapies can be defined as temporal phenotyping resulting from changes in morphological (tumor staging), biochemical (biomarker testing), physiological (disease progression), ...
Source: Journal of Biomedical Informatics - November 2, 2019 Category: Information Technology Source Type: research

Time-to-Event Estimation by Re-defining Time
Publication date: Available online 31 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Xi Hang Cao, Chao Han, Lucas M Glass, Allen Kindman, Zoran ObradovicAbstractThe primary goal of a time-to-event estimation model is to accurately infer the occurrence time of a target event. Most existing studies focus on developing new models to effectively utilize the information in the censored observations. In this paper, we propose a model to tackle the time-to-event estimation problem from a completely different perspective. Our model relaxes a fundamental constraint that the target variable, time, is a univariate nu...
Source: Journal of Biomedical Informatics - November 2, 2019 Category: Information Technology Source Type: research

Deep Learning Predicts Extreme Preterm Birth from Electronic Health Records
ConclusionTemporal deep learning can predict EPB up to 8 weeks earlier than its occurrence. Accurate prediction of EPB may allow healthcare organizations to allocate resources effectively and ensure patients receive appropriate care.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - November 2, 2019 Category: Information Technology Source Type: research

Sex, Obesity, Diabetes, and Exposure to Particulate Matter among Patients with Severe Asthma: Scientific Insights from a Comparative Analysis of Open Clinical Data Sources during a Five-day Hackathon
Publication date: Available online 30 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Karamarie Fecho, Stanley C. Ahalt, Saravanan Arunachalam, James Champion, Christopher G. Chute, Sarah Davis, Kenneth Gersing, Gustavo Glusman, Jennifer Hadlock, Jewel Lee, Emily Pfaff, Max Robinson, Eric Sid, Casey Ta, Hao Xu, Richard Zhu, Qian Zhu, David B. Peden, The Biomedical Data Translator ConsortiumAbstractThis special communication describes activities, products, and lessons learned from a recent hackathon that was funded by the National Center for Advancing Translational Sciences via the Biomedical Data Translator...
Source: Journal of Biomedical Informatics - November 1, 2019 Category: Information Technology Source Type: research

Quantifying Semantic Similarity of Clinical Evidence in the Biomedical Literature to Facilitate Related Evidence Synthesis
ConclusionExperimental results showed that the proposed semantic similarity quantification approach can effectively identify related clinical evidence that is reported in the literature. The comparison with a state-of-the-art method demonstrated the effectiveness of the approach, and experiments with an external dataset support its generalisability.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - November 1, 2019 Category: Information Technology Source Type: research

DiseaSE: A Biomedical Text Analytics System for Disease Symptom Extraction and Characterization
Publication date: Available online 31 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Muhammad Abulaish, Md. Aslam Parwez, JahiruddinAbstractDue to increasing volume and unstructured nature of the scientific literatures in biomedical domain, most of the information embedded within them remain untapped. This paper presents a biomedical text analytics system, DiseaSE (Disease Symptom Extraction), to identify and extract disease symptoms and their associations from biomedical text documents retrieved from the PubMed database. It implements various NLP and information extraction techniques to convert text docum...
Source: Journal of Biomedical Informatics - November 1, 2019 Category: Information Technology Source Type: research

Automated Grouping of Medical Codes via Multiview Banded Spectral Clustering
ConclusionThe proposed approach, by systematically leveraging multiple data sources, is able to overcome bias while maximizing consensus to achieve generalizability. It has the advantage of being efficient, scalable, and adaptive to the evolving human knowledge reflected in the data, showing a significant step toward automating medical knowledge integration. (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - October 30, 2019 Category: Information Technology Source Type: research

Using Machine Learning to Selectively Highlight Patient Information
ConclusionData-driven approaches for adaptively displaying data in EMR systems, like the LEMR system, show promise in using information-seeking behavior of clinicians to identify and highlight relevant patient data.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - October 30, 2019 Category: Information Technology Source Type: research

Augmenting cancer cell proteomics with cellular images – a semantic approach to understand focal adhesion
Publication date: Available online 24 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Thomas J. Bauer, Erich Gombocz, Marcus Krüger, Jayashree Sahana, Thomas J. Corydon, Johann Bauer, Manfred Infanger, Daniela GrimmAbstractIf monolayers of cancer cells are exposed to microgravity, some of the cells cease adhering to the bottom of a culture flask and join three-dimensional aggregates floating in the culture medium. Searching reasons for this change in phenotype, we performed proteome analyses and learnt that accumulation and posttranslational modification of proteins involved in cell-matrix and cell-cel...
Source: Journal of Biomedical Informatics - October 26, 2019 Category: Information Technology Source Type: research

Touchless interaction with medical images based on 3D hand cursors supported by single-foot input: a case study in dentistry
Publication date: Available online 24 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Soraia Figueiredo Paulo, Filipe Relvas, Hugo Nicolau, Yosra Rekik, Vanessa Machado, João Botelho, José João Mendes, Laurent Grisoni, Joaquim Jorge, Daniel Simões LopesAbstractFeet input can support mid-air hand gestures for touchless medical image manipulation to prevent unintended activations, especially in sterile contexts. However, foot interaction has yet to be investigated in dental settings. In this paper, we conducted a mixed methods research study with medical dentistry professionals. To...
Source: Journal of Biomedical Informatics - October 26, 2019 Category: Information Technology Source Type: research

A Naked Eye 3D Display and Interaction System for Medical Education and Training
Publication date: Available online 23 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Guowen Chen, Tianqi Huang, Zhencheng Fan, Xinran Zhang, Hongen LiaoAbstractTo provide natural simulated objects and intuitive user interaction in medical education and training, we propose a naked eye 3D display and interaction system. The current 3D rendering algorithms for naked eye 3D displays are not suitable for medical use, due to the requirements of displaying and interacting with high quality medical images and simulating soft tissues. Because the traditional 3D rendering procedure and vertex indexing in collision ...
Source: Journal of Biomedical Informatics - October 24, 2019 Category: Information Technology Source Type: research

Machine learning and Bioinformatics Models to Identify Gene Expression Patterns of Ovarian Cancer Associated with Disease Progression and Mortality
Publication date: Available online 23 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Md. Ali Hossain, Sheikh Muhammad Saiful Islam, Julian M.W. Quinn, Fazlul Huq, Mohammad Ali MoniAbstractOvarian cancer (OC) is a common cause of cancer death among women worldwide, so there is a pressing need to identify factors influencing OC mortality. Much OC patient clinical data is publicly accessible via the Broad Institute Cancer Genome Atlas (TCGA) datasets which include patient age, cancer site, stage and subtype and patient survival, as well as OC gene transcription profiles. These allow studies correlation of OC ...
Source: Journal of Biomedical Informatics - October 24, 2019 Category: Information Technology Source Type: research

Ensembles of Natural Language Processing Systems for Portable Phenotyping Solutions
ConclusionsOur study demonstrates that ensembles of natural language processing can improve both generic phenotypic concept recognition and patient specific phenotypic concept identification over individual systems. Among the individual NLP systems, each individual system performed best when they were applied in the dataset that they were primary designed for. However, combining multiple NLP systems to create an ensemble can generally improve the performance. Specifically, the ensemble can increase the results reproducibility across different cohorts and tasks, and thus provide a more portable phenotyping solution compared...
Source: Journal of Biomedical Informatics - October 24, 2019 Category: Information Technology Source Type: research

Inter-observer agreement and reliability assessment for observational studies of clinical work
We present a combination of methods that simultaneously addresses both these issues and provides a more appropriate measure by which to assess IOA for time-and-motion studies. The issue of alignment is addressed by converting task-level data into small time windows then aligning data from different observers by time. A method applicable to multivariate nominal data, the iota score, is then applied to the time-aligned data. We illustrate our approach by comparing iota scores to the mean of univariate Cohen’s kappa scores through application of these measures to existing data from an observational study of emergency de...
Source: Journal of Biomedical Informatics - October 23, 2019 Category: Information Technology Source Type: research

Beyond TAM and UTAUT: Future directions for HIT implementation research
Publication date: Available online 17 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Aviv Shachak, Craig Kuziemsky, Carolyn PetersenAbstractThe Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) have been used widely in studies of health information technology (HIT) implementation. However, TAM and UTAUT have also been criticized for being overly simplistic (TAM) and for taking a narrow perspective, which focuses only on individual adopters’ beliefs, perceptions and usage intention. Furthermore, with thousands of studies using these theories, their contri...
Source: Journal of Biomedical Informatics - October 17, 2019 Category: Information Technology Source Type: research

Transforming Healthcare with Big Data Analytics and Artificial Intelligence: A Systematic Mapping Study
Publication date: Available online 17 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Nishita Mehta, Anil Pandit, Sharvari ShuklaAbstractThe domain of healthcare has always been flooded with a huge amount of complex data, coming in at a very fast-pace. A vast amount of data is generated in different sectors of healthcare industry: data from hospitals and healthcare providers, medical insurance, medical equipment, life sciences and medical research. With the advancement in technology, there is a huge potential for utilization of this data for transforming healthcare. The application of analytics, machine lea...
Source: Journal of Biomedical Informatics - October 17, 2019 Category: Information Technology Source Type: research

A Method for the Graphical Modeling of Relative Temporal Constraints
We describe how to generate database queries from this notation. We provide a prototypical implementation, consisting of a temporal query modeling frontend and an experimental backend that connects to an i2b2 system. We evaluate our modeling approach on the MIMIC-III database to demonstrate that it can be used for modeling typical temporal phenotyping queries.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - October 17, 2019 Category: Information Technology Source Type: research

RedMed: Extending drug lexicons for social media applications
Publication date: Available online 15 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Adam Lavertu, Russ B AltmanAbstractSocial media has been identified as a promising potential source of information for pharmacovigilance. The adoption of social media data has been hindered by the massive and noisy nature of the data. Initial attempts to use social media data have relied on exact text matches to drugs of interest, and therefore suffer from the gap between formal drug lexicons and the informal nature of social media. The Reddit comment archive represents an ideal corpus for bridging this gap. We trained a w...
Source: Journal of Biomedical Informatics - October 17, 2019 Category: Information Technology Source Type: research

Using the PARAFAC2 Tensor Factorization on EHR Audit Data to Understand PCP Desktop Work
ConclusionsOur results demonstrate that EHR audit log data can be rapidly processed to create higher-level constructed features that represent time-stamped PCP tasks.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - October 17, 2019 Category: Information Technology Source Type: research

Phenotypic similarity for rare disease: ciliopathy diagnoses and subtyping
Publication date: Available online 14 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Xiaoyi Chen, Nicolas Garcelon, Antoine Neuraz, Katy Billot, Marc Lelarge, Thomas Bonald, Hugo Garcia, Yoann Martin, Vincent Benoit, Marc Vincent, Hassan Faour, Maxime Douillet, Stanislas Lyonnet, Sophie Saunier, Anita BurgunAbstractRare diseases are often hard and long to be diagnosed precisely, and most of them lack approved treatment. For some complex rare diseases, precision medicine approach is further required to stratify patients into homogeneous subgroups based on the clinical, biological or molecular features. In s...
Source: Journal of Biomedical Informatics - October 15, 2019 Category: Information Technology Source Type: research

Associative Attention Networks for Temporal Relation Extraction from Electronic Health Records
Publication date: Available online 15 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Shiyi Zhao, Lishuang Li, Hongbin Lu, Anqiao Zhou, Shuang QianAbstractTemporal relations are crucial in constructing a timeline over the course of clinical care, which can help medical practitioners and researchers track the progression of diseases, treatments and adverse reactions over time. Due to the rapid adoption of Electronic Health Records (EHRs) and high cost of manual curation, using Natural Language Processing (NLP) to extract temporal relations automatically has become a promising approach. Typically temporal rel...
Source: Journal of Biomedical Informatics - October 15, 2019 Category: Information Technology Source Type: research

Comparing Information Extraction Techniques for Low-Prevalence Concepts: The Case of Insulin Rejection by Patients
ConclusionsIdentification of low-prevalence concepts can present challenges in medical language processing. Rule-based systems that include the designer’s background knowledge of language may be able to achieve higher accuracy under these circumstances.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - October 14, 2019 Category: Information Technology Source Type: research

Developing a FHIR-based EHR Phenotyping Framework: A Case Study for Identification of Patients with Obesity and Multiple Comorbidities from Discharge Summaries
ConclusionsThe study demonstrated that the FHIR-based EHR phenotyping approach could effectively identify the state of obesity and multiple comorbidities using semi-structured discharge summaries. Our FHIR-based phenotyping approach is a first concrete step towards improving the data aspect of phenotyping portability across EHR systems and enhancing interpretability of the machine learning-based phenotyping algorithms.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - October 14, 2019 Category: Information Technology Source Type: research

PARS, a system combining semantic technologies with multiple criteria decision aiding for supporting antibiotic prescriptions
Publication date: Available online 14 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Souhir Ben Souissi, Mourad Abed, Lahcen El Hiki, Philippe Fortemps, Marc PirlotAbstractObjectiveMotivated by the well documented worldwide spread of adverse drug events, as well as the increased danger of antibiotic resistance (caused mainly by inappropriate prescribing and overuse), we propose a novel recommendation system for antibiotic prescription (PARS).MethodOur approach is based on the combination of semantic technologies with MCDA (Multiple Criteria Decision Aiding) that allowed us to build a two level decision sup...
Source: Journal of Biomedical Informatics - October 14, 2019 Category: Information Technology Source Type: research

Microservice chatbot architecture for chronic patient support
Publication date: Available online 14 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Surya Roca, Jorge Sancho, José García, Álvaro AlesancoAbstractChatbots are able to provide support to patients suffering from very different conditions. Patients with chronic diseases or comorbidities could benefit the most from chatbots which can keep track of their condition, provide specific information, encourage adherence to medication, etc. To perform these functions, chatbots need a suitable underlying software architecture. In this paper, we introduce a chatbot architecture for chronic patient ...
Source: Journal of Biomedical Informatics - October 14, 2019 Category: Information Technology Source Type: research

A trade-off dual-factor model to investigate discontinuous intention of health app users: From the perspective of information disclosure
Publication date: Available online 12 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Cheng-Kui Huang Tony, Shin-Horng Chen, Chia-Pei Tang, Hsin-Ying HuangAbstractNumerous mobile apps have been developed for making our lives more convenient and improving our quality of life. Health apps are among them. These types of apps are designed to help users for recording their health-related behaviors and to give advice about improving users’ physical conditions. However, users frequently do not continue to use these health apps. As a result, the companies of health apps have paid the development cost but cann...
Source: Journal of Biomedical Informatics - October 14, 2019 Category: Information Technology Source Type: research

Deep Representation Learning for Individualized Treatment Effect Estimation using Electronic Health Records
Publication date: Available online 11 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Peipei Chen, Wei Dong, Xudong Lu, Uzay Kaymak, Kunlun He, Zhengxing HuangAbstractUtilizing clinical observational data to estimate individualized treatment effects (ITE) is a challenging task, as confounding inevitably exists in clinical data. Most of the existing models for ITE estimation tackle this problem by creating unbiased estimators of the treatment effects. Although valuable, learning a balanced representation is sometimes directly opposed to the objective of learning an effective and discriminative model for ITE ...
Source: Journal of Biomedical Informatics - October 12, 2019 Category: Information Technology Source Type: research

Cover 1/Spine
Publication date: October 2019Source: Journal of Biomedical Informatics, Volume 98Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - October 5, 2019 Category: Information Technology Source Type: research

Cover 2: Editorial Board
Publication date: October 2019Source: Journal of Biomedical Informatics, Volume 98Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - October 5, 2019 Category: Information Technology Source Type: research

fmi-ii: Table of Contents
Publication date: October 2019Source: Journal of Biomedical Informatics, Volume 98Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - October 5, 2019 Category: Information Technology Source Type: research

fmiii: Copyright/ID Statement
Publication date: October 2019Source: Journal of Biomedical Informatics, Volume 98Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - October 5, 2019 Category: Information Technology Source Type: research

A frame semantic overview of NLP-based information extraction for cancer-related EHR notes
ConclusionThe list of common frames described in this paper identifies important cancer-related information extracted by existing NLP techniques and serves as a useful resource for future researchers requiring cancer information extracted from EHR notes. We also argue, due to the heavy duplication of cancer NLP systems, that a general purpose resource of annotated cancer frames and corresponding NLP tools would be valuable.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - October 5, 2019 Category: Information Technology Source Type: research

Extracting drug–drug interactions with hybrid bidirectional gated recurrent unit and graph convolutional network
Publication date: Available online 27 September 2019Source: Journal of Biomedical InformaticsAuthor(s): Di Zhao, Jian Wang, Hongfei Lin, Zhihao Yang, Yijia ZhangAbstractDrug–drug interactions are critical in studying drug side effects. Thus, quickly and accurately identifying the relationship between drugs is necessary. Current methods for biomedical relation extraction include only the sequential information of sentences, while syntactic graph representations have not been explored in DDI extraction. We herein present a novel hybrid model to extract a biomedical relation that combines a bidirectional gated recurrent...
Source: Journal of Biomedical Informatics - September 28, 2019 Category: Information Technology Source Type: research

Patient Clustering Improves Efficiency of Federated Machine Learning to Predict Mortality and Hospital Stay Time Using Distributed Electronic Medical Records
Publication date: Available online 24 September 2019Source: Journal of Biomedical InformaticsAuthor(s): Li Huang, Andrew L. Shea, Huining Qian, Aditya Masurkar, Hao Deng, Dianbo LiuAbstractElectronic medical records (EMRs) support the development of machine learning algorithms for predicting disease incidence, patient response to treatment, and other healthcare events. But so far most algorithms have been centralized, taking little account of the decentralized, non-identically independently distributed (non-IID), and privacy-sensitive characteristics of EMRs that can complicate data collection, sharing and learning. To add...
Source: Journal of Biomedical Informatics - September 25, 2019 Category: Information Technology Source Type: research

Wikidata: A large-scale collaborative ontological medical database
Publication date: Available online 23 September 2019Source: Journal of Biomedical InformaticsAuthor(s): Houcemeddine Turki, Thomas Shafee, Mohamed Ali Hadj Taieb, Mohamed Ben Aouicha, Denny Vrandečić, Diptanshu Das, Helmi HamdiAbstractCreated in October 2012, Wikidata is a large-scale, human-readable, machine-readable, multilingual, multidisciplinary, centralized, editable, structured, and linked knowledge-base with an increasing diversity of use cases. Here, we raise awareness of the potential use of Wikidata as a useful resource for biomedical data integration and semantic interoperability between biomedical computer s...
Source: Journal of Biomedical Informatics - September 25, 2019 Category: Information Technology Source Type: research

Adversarial Training Based Lattice LSTM for Chinese Clinical Named Entity Recognition
Publication date: Available online 23 September 2019Source: Journal of Biomedical InformaticsAuthor(s): Shan Zhao, Zhiping Cai, Haiwen Chen, Ye Wang, Fang Liu, Anfeng LiuAbstractClinical named entity recognition (CNER), which intends to automatically detect clinical entities in electronic health record (EHR), is a committed step for further clinical text mining. Recently, more and more deep learning models are used to Chinese CNER. However, these models do not make full use of the information in EHR, for these models are either word-based or character-based. In addition, neural models tend to be locally unstable and even t...
Source: Journal of Biomedical Informatics - September 25, 2019 Category: Information Technology Source Type: research

Neural network-based approaches for biomedical relation classification: A review
We present the general framework for neural network-based approaches in biomedical relation extraction and pretrained word embedding resources. We discuss neural network-based approaches, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). We conclude by describing the remaining challenges and outlining future directions.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - September 23, 2019 Category: Information Technology Source Type: research

A two-stage deep learning approach for extracting entities and relationships from medical texts
Publication date: Available online 20 September 2019Source: Journal of Biomedical InformaticsAuthor(s): Víctor Suárez-Paniagua, Renzo M. Rivera Zavala, Isabel Segura-Bedmar, Paloma MartínezAbstractThis work presents a two-stage deep learning system for Named Entity Recognition (NER) and Relation Extraction (RE) from medical texts. These tasks are a crucial step to many natural language understanding applications in the biomedical domain. Automatic medical coding of electronic medical records, automated summarizing of patient records, automatic cohort identification for clinical studies, text simplifica...
Source: Journal of Biomedical Informatics - September 22, 2019 Category: Information Technology Source Type: research

Making work visible for electronic phenotype implementation: lessons learned from the eMERGE network
ConclusionThis study presents firsthand knowledge of the substantial implementation efforts in phenotyping and introduces a novel metric (KIP) to measure portability of phenotype algorithms for quantifying such efforts across the eMERGE Network. Phenotype developers are encouraged to analyze and optimize the portability in regards to knowledge, interpretation and programming. CDMs can be used to improve the portability for some ‘knowledge-oriented’ tasks.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - September 20, 2019 Category: Information Technology Source Type: research

Chinese Clinical Named Entity Recognition with Radical-Level Feature and Self-Attention Mechanism
Publication date: Available online 18 September 2019Source: Journal of Biomedical InformaticsAuthor(s): Mingwang Yin, Chengjie Mou, Kaineng Xiong, Jiangtao RenAbstractNamed entity recognition is a fundamental and crucial task in medical natural language processing problems. In medical fields, Chinese clinical named entity recognition identifies boundaries and types of medical entities from unstructured text such as electronic medical records. Recently, a composition model of bidirectional Long Short-term Memory Networks(BiLSTMs) and conditional random field (BiLSTM-CRF) based character-level semantics has achieved great su...
Source: Journal of Biomedical Informatics - September 19, 2019 Category: Information Technology Source Type: research

An Empirical Study on Prediction of Population Health through Social Media
Publication date: Available online 12 September 2019Source: Journal of Biomedical InformaticsAuthor(s): Hung Nguyen, Thin Nguyen, Duc Thanh NguyenAbstractPublic health measurement is important for government administration as it provides indicators and implications to public healthcare strategies. The measurement of health status has been traditionally conducted via surveys in the forms of pre-designed questionnaires to collect responses from targeted participants. Apart from benefits, traditional approach is costly, time-consuming, and not scalable. These limitations make a major obstacle to policy makers to develop up-to...
Source: Journal of Biomedical Informatics - September 13, 2019 Category: Information Technology Source Type: research