Read by QxMD icon Read

Journal of Biomedical Informatics

Rodney A Gabriel, Tsung-Ting Kuo, Julian McAuley, Chun-Nan Hsu
BACKGROUND: Big clinical note datasets found in electronic health records (EHR) present substantial opportunities to train accurate statistical models that identify patterns in patient diagnosis and outcomes. However, near-to-exact duplication in note texts is a common issue in many clinical note datasets. We aimed to use a scalable algorithm to de-duplicate notes and further characterize the sources of duplication. METHODS: We use an approximation algorithm to minimize pairwise comparisons consisting of three phases: 1) Minhashing with Locality Sensitive Hashing; 2) a clustering method using tree-structured disjoint sets; and 3) classification of near-duplicates (exact copies, common machine output notes, or similar notes) via pairwise comparison of notes in each cluster...
April 18, 2018: Journal of Biomedical Informatics
Jérémie Decouchant, Maria Fernandes, Marcus Völp, Francisco M Couto, Paulo Esteves-Veríssimo
Sequencing thousands of human genomes has enabled breakthroughs in many areas, among them precision medicine, the study of rare diseases, and forensics. However, mass collection of such sensitive data entails enormous risks if not protected to the highest standards. In this article, we follow the position and argue that post-alignment privacy is not enough and that data should be automatically protected as early as possible in the genomics workflow, ideally immediately after the data is produced. We show that a previous approach for filtering short reads cannot extend to long reads and present a novel filtering approach that classifies raw genomic data (i...
April 13, 2018: Journal of Biomedical Informatics
Moumita Bhattacharya, Claudine Jurkovitz, Hagit Shatkay
Patients associated with multiple co-occurring health conditions often face aggravated complications and less favorable outcomes. Co-occurring conditions are especially prevalent among individuals suffering from kidney disease, an increasingly widespread condition affecting 13% of the general population in the US. This study aims to identify and characterize patterns of co-occurring medical conditions in patients employing a probabilistic framework. Specifically, we apply topic modeling in a non-traditional way to find associations across SNOMED-CT codes assigned and recorded in the EHRs of >13,000 patients diagnosed with kidney disease...
April 12, 2018: Journal of Biomedical Informatics
Asma Pashazadeh, Nima Jafari Navimipour
Healthcare provides many services such as diagnosing, treatment, prevention of diseases, illnesses, injuries, and other physical and mental disorders. Large-scale distributed data processing applications in healthcare as a basic concept operates on large amounts of data. Therefore, big data application functions are the main part of healthcare operations, but there was not any comprehensive and systematic survey about studying and evaluating the important techniques in this field. Therefore, this paper aims at providing the comprehensive, detailed, and systematic study of the state-of-the-art mechanisms in the big data related to healthcare applications in five categories, including machine learning, cloud-based, heuristic-based, agent-based, and hybrid mechanisms...
April 12, 2018: Journal of Biomedical Informatics
Signe H Kragelund, Mona Kjærsgaard, Søren Jensen-Fangel, Rita A Leth, Nina Ank
The aim of this study was to develop an audit tool with a built-in database using Research Electronic Data Capture (REDCap®) as part of an antimicrobial stewardship program at a regional hospital in the Central Denmark Region, and to analyse the need, if any, to involve more than one expert in the evaluation of cases of antimicrobial treatment, and the level of agreement among the experts. Patients treated with systemic antimicrobials in the period from 1 September 2015 to 31 August 2016 were included, in total 722 cases...
April 9, 2018: Journal of Biomedical Informatics
Leila Safari, Jon D Patrick
PURPOSE: This paper reports on a generic framework to provide clinicians with the ability to conduct complex analyses on elaborate research topics using cascaded queries to resolve internal time-event dependencies in the research questions, as an extension to the proposed Clinical Data Analytics Language (CliniDAL). METHODS: A cascaded query model is proposed to resolve internal time-event dependencies in the queries which can have up to five levels of criteria starting with a query to define subjects to be admitted into a study, followed by a query to define the time span of the experiment...
April 9, 2018: Journal of Biomedical Informatics
Enver Zerem, Suad Kunosić
No abstract text is available yet for this article.
April 6, 2018: Journal of Biomedical Informatics
Angel Jimenez-Molina, Jorge Gaete-Villegas, Javier Fuentes
New advances in telemedicine, ubiquitous computing, and artificial intelligence have supported the emergence of more advanced applications and support systems for chronic patients. This trend addresses the important problem of chronic illnesses, highlighted by multiple international organizations as a core issue in future healthcare. Despite the myriad of exciting new developments, each application and system is designed and implemented for specific purposes and lacks the flexibility to support different healthcare concerns...
April 5, 2018: Journal of Biomedical Informatics
Don A Vaughn, Welmoed K van Deen, Wesley T Kerr, Travis R Meyer, Andrea L Bertozzi, Daniel W Hommes, Mark S Cohen
OBJECTIVE: Inflammatory Bowel Disease (IBD) is an inflammatory disorder of the gastrointestinal tract that can necessitate hospitalization and the use of expensive biologics. Models predicting these interventions may improve patient quality of life and reduce expenditures. MATERIALS AND METHODS: We used insurance claims from 2011-2013 to predict IBD-related hospitalizations and the initiation of biologics. We derived and optimized our model from a 2011 training set of 7771 members, predicting their outcomes the following year...
April 3, 2018: Journal of Biomedical Informatics
Farnaz Sabahi
Rooted deeply in medical multiple criteria decision-making (MCDM), risk assessment is very important especially when applied to the risk of being affected by deadly diseases such as coronary heart disease (CHD). CHD risk assessment is a stochastic, uncertain, and highly dynamic process influenced by various known and unknown variables. In recent years, there has been a great interest in fuzzy analytic hierarchy process (FAHP), a popular methodology for dealing with uncertainty in MCDM. This paper proposes a new FAHP, bimodal fuzzy analytic hierarchy process (BFAHP) that augments two aspects of knowledge, probability and validity, to fuzzy numbers to better deal with uncertainty...
April 3, 2018: Journal of Biomedical Informatics
Yijia Zhang, Hongfei Lin, Zhihao Yang, Jian Wang, Shaowu Zhang, Yuanyuan, Sun, Liang Yang
Biomedical relation extraction can automatically extract high-quality biomedical relations from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in the literature. Recurrent neural networks (RNNs) and convolutional neural networks (CNNs) are two major neural network models for biomedical relation extraction. Neural network-based methods for biomedical relation extraction typically focus on the sentence sequence and employ RNNs or CNNs to learn the latent features from sentence sequences separately...
March 27, 2018: Journal of Biomedical Informatics
Patrick J Trainor, Roman V Yampolskiy, Andrew P DeFilippis
INTRODUCTION: Heart disease remains a leading cause of global mortality. While acute myocardial infarction (colloquially: heart attack), has multiple proximate causes, proximate etiology cannot be determined by a blood-based diagnostic test. We enrolled a suitable patient cohort and conducted a non-targeted quantification of plasma metabolites by mass spectrometry for developing a test that can differentiate between thrombotic MI, non-thrombotic MI, and stable disease. A significant challenge in developing such a diagnostic test is solving the NP-hard problem of feature selection for constructing an optimal statistical classifier...
March 22, 2018: Journal of Biomedical Informatics
Chaoxing Li, Valentin Dinu
MicroRNAs (miRNAs) are small, non-coding RNAs involved in the regulation of gene expression at a post-transcriptional level. Recent studies have shown miRNAs as key regulators of a variety of biological processes, such as proliferation, differentiation, apoptosis, metabolism, etc. Aberrantly expressed miRNAs influence individual gene expression level, but rewired miRNA-mRNA connections can influence the activity of biological pathways. Here, we define rewired miRNA-mRNA connections as the differential (rewiring) effects on the activity of biological pathways between hepatocellular carcinoma (HCC) and normal phenotypes...
March 22, 2018: Journal of Biomedical Informatics
Ozra Nikdelfaz, Saeed Jalili
Predicting disease candidate genes from human genome is a crucial part of nowadays biomedical research. According to observations, diseases with the same phenotype have the similar biological characteristics and genes associated with these same diseases tend to share common functional properties. Therefore, by applying machine learning methods, new disease genes are predicted based on previous ones. In recent studies, some semi-supervised learning methods, called Positive-Unlabeled Learning (PU-Learning) are used for predicting disease candidate genes...
March 20, 2018: Journal of Biomedical Informatics
Rajko Igić
No abstract text is available yet for this article.
March 17, 2018: Journal of Biomedical Informatics
Kalia Orphanou, Arianna Dagliati, Lucia Sacchi, Athena Stassopoulou, Elpida Keravnou, Riccardo Bellazzi
In this paper, we develop a Naïve Bayes classification model integrated with temporal association rules (TARs). A temporal pattern mining algorithm is used to detect TARs by identifying the most frequent temporal relationships among the derived basic temporal abstractions (TA). We develop and compare three classifiers that use as features the most frequent TARs as follows: i) representing the most frequent TARs detected within the target class ('Disease = Present'), ii) representing the most frequent TARs from both classes ('Disease = Present', 'Disease = Absent'), iii) representing the most frequent TARs, after removing the ones that are low-risk predictors for the disease...
March 16, 2018: Journal of Biomedical Informatics
Ane Alberdi Aramendi, Alyssa Weakley, Asier Aztiria Goenaga, Maureen Schmitter-Edgecombe, Diane J Cook
In the context of an aging population, tools to help elderly to live independently must be developed. The goal of this paper is to evaluate the possibility of using unobtrusively collected activity-aware smart home behavioral data to automatically detect one of the most common consequences of aging: functional health decline. After gathering the longitudinal smart home data of 29 older adults for an average of > 2 years, we automatically labeled the data with corresponding activity classes and extracted time-series statistics containing 10 behavioral features...
March 15, 2018: Journal of Biomedical Informatics
Qindong Sun, Nan Wang, Shancang Li, Hongyi Zhou
Recently, the online social networks (OSNs) have received considerable attentions as a revolutionary platform to offer users massive social interaction among users that enables users to be more involved in their own healthcare. The OSNs have also promoted increasing interests in the generation of analytical, data models in health informatics. This paper aims at developing an obesity identification, analysis, and estimation model, in which each individual user is regarded as an online social network 'sensor' that can provide valuable health information...
March 15, 2018: Journal of Biomedical Informatics
Chun-Fu Hong, Ying-Chen Chen, Wei-Chun Chen, Keng-Chang Tu, Meng-Hsiun Tsai, Yung-Kuan Chan, Shyr Shen Yu
A microarray analysis generally contains expression data of thousands of genes, but most of them are irrelevant to the disease of interest, making analyzing the genes concerning specific diseases complicated. Therefore, filtering out a few essential genes as well as their regulatory networks is critical, and a disease can be easily diagnosed just depending on the expression profiles of a few critical genes. In this study, a target gene screening (TGS) system, which is a microarray-based information system that integrates F-statistics, pattern recognition matching, a two-layer K-means classifier, a Parameter Detection Genetic Algorithm (PDGA), a genetic-based gene selector (GBG selector) and the association rule, was developed to screen out a small subset of genes that can discriminate malignant stages of cancers...
March 14, 2018: Journal of Biomedical Informatics
Mohammad Zahidul Hasan, Md Safiur Rahman Mahdi, Md Nazmus Sadat, Noman Mohammed
Human genomic information can yield more effective healthcare by guiding medical decisions. Therefore, genomics research is gaining popularity as it can identify potential correlations between a disease and a certain gene, which improves the safety and efficacy of drug treatment and can also develop more effective prevention strategies [1]. To reduce the sampling error and to increase the statistical accuracy of this type of research projects, data from different sources need to be brought together since a single organization does not necessarily possess required amount of data...
March 14, 2018: Journal of Biomedical Informatics
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"