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https://www.readbyqxmd.com/read/29792082/mining-concepts-of-health-responsibility-using-text-mining-and-exploratory-graph-analysis
#1
Sofia Kjellström, Hudson Golino
BACKGROUND: Occupational therapists need to know about people's beliefs about personal responsibility for health to help them pursue everyday activities. AIM: The study aims to employ state-of-the-art quantitative approaches to understand people's views of health and responsibility at different ages. METHODS: A mixed method approach was adopted, using text mining to extract information from 233 interviews with participants aged 5 to 96 years, and then exploratory graph analysis to estimate the number of latent variables...
May 24, 2018: Scandinavian Journal of Occupational Therapy
https://www.readbyqxmd.com/read/29788413/eztag-tagging-biomedical-concepts-via-interactive-learning
#2
Dongseop Kwon, Sun Kim, Chih-Hsuan Wei, Robert Leaman, Zhiyong Lu
Recently, advanced text-mining techniques have been shown to speed up manual data curation by providing human annotators with automated pre-annotations generated by rules or machine learning models. Due to the limited training data available, however, current annotation systems primarily focus only on common concept types such as genes or diseases. To support annotating a wide variety of biological concepts with or without pre-existing training data, we developed ezTag, a web-based annotation tool that allows curators to perform annotation and provide training data with humans in the loop...
May 18, 2018: Nucleic Acids Research
https://www.readbyqxmd.com/read/29782036/differential-diagnosis-of-jaw-pain-using-informatics-technology
#3
Yoon Nam, Hong-Gee Kim, Hong-Seop Kho
This study aimed to deduce evidence-based clinical clues that differentiate temporomandibular disorders (TMD)-mimicking conditions from genuine TMD by text mining using natural language processing (NLP) and recursive partitioning. We compared the medical records of 29 patients diagnosed with TMD-mimicking conditions and 290 patients diagnosed with genuine TMD. Chief complaints and medical histories were preprocessed via NLP to compare the frequency of word usage. In addition, recursive partitioning was used to deduce the optimal size of mouth opening, which could differentiate TMD-mimicking from genuine TMD groups...
May 21, 2018: Journal of Oral Rehabilitation
https://www.readbyqxmd.com/read/29776534/an-investigation-into-online-videos-as-a-source-of-safety-hazard-reports
#4
Leila Nasri, Milad Baghersad, Richard Gruss, Nico Sung Won Marucchi, Alan S Abrahams, Johnathon P Ehsani
INTRODUCTION: Despite the advantages of video-based product reviews relative to text-based reviews in detecting possible safety hazard issues, video-based product reviews have received no attention in prior literature. This study focuses on online video-based product reviews as possible sources to detect safety hazards. METHODS: We use two common text mining methods - sentiment and smoke words - to detect safety issues mentioned in videos on the world's most popular video sharing platform, YouTube...
June 2018: Journal of Safety Research
https://www.readbyqxmd.com/read/29775406/phrase-mining-of-textual-data-to-analyze-extracellular-matrix-protein-patterns-across-cardiovascular-disease
#5
David Alexandre Liem, Sanjana Murali, Dibakar Sigdel, Yu Shi, Xuan Wang, Jiaming Shen, Howard Choi, J Harry Caufield, Wei Wang, Peipei Ping, Jiawei Han
Extracellular matrix (ECM) proteins have been shown to play important roles regulating multiple biological processes in an array of organ systems, including the cardiovascular system. By using a novel bioinformatics text-mining tool, we studied six categories of cardiovascular disease (CVD), namely ischemic heart disease (IHD), cardiomyopathies (CM), cerebrovascular accident (CVA), congenital heart disease (CHD), arrhythmias (ARR), and valve disease (VD), anticipating novel ECM protein-disease and protein-protein relationships hidden within vast quantities of textual data...
May 18, 2018: American Journal of Physiology. Heart and Circulatory Physiology
https://www.readbyqxmd.com/read/29763853/text-mining-and-network-analysis-to-find-functional-associations-of-genes-in-high-altitude-diseases
#6
Balu Bhasuran, Devika Subramanian, Jeyakumar Natarajan
BACKGROUND AND OBJECTIVES: Travel to elevations above 2500 m is associated with the risk of developing one or more forms of acute altitude illness such as acute mountain sickness (AMS), high altitude cerebral edema (HACE) or high altitude pulmonary edema (HAPE). Our work aims to identify the functional association of genes involved in high altitude diseases. METHOD: In this work we identified the gene networks responsible for high altitude diseases by using the principle of gene co-occurrence statistics from literature and network analysis...
May 2, 2018: Computational Biology and Chemistry
https://www.readbyqxmd.com/read/29762787/litvar-a-semantic-search-engine-for-linking-genomic-variant-data-in-pubmed-and-pmc
#7
Alexis Allot, Yifan Peng, Chih-Hsuan Wei, Kyubum Lee, Lon Phan, Zhiyong Lu
The identification and interpretation of genomic variants play a key role in the diagnosis of genetic diseases and related research. These tasks increasingly rely on accessing relevant manually curated information from domain databases (e.g. SwissProt or ClinVar). However, due to the sheer volume of medical literature and high cost of expert curation, curated variant information in existing databases are often incomplete and out-of-date. In addition, the same genetic variant can be mentioned in publications with various names (e...
May 14, 2018: Nucleic Acids Research
https://www.readbyqxmd.com/read/29753874/simulation-of-patient-flow-in-multiple-healthcare-units-using-process-and-data-mining-techniques-for-model-identification
#8
Sergey V Kovalchuk, Anastasia A Funkner, Oleg G Metsker, Aleksey N Yakovlev
INTRODUCTION: An approach to building a hybrid simulation of patient flow is introduced with a combination of data-driven methods for automation of model identification. The approach is described with a conceptual framework and basic methods for combination of different techniques. The implementation of the proposed approach for simulation of the acute coronary syndrome (ACS) was developed and used in an experimental study. METHODS: A combination of data, text, process mining techniques, and machine learning approaches for the analysis of electronic health records (EHRs) with discrete-event simulation (DES) and queueing theory for the simulation of patient flow was proposed...
May 10, 2018: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/29751809/lessons-learned-from-ideal-33-recommendations-from-the-ideal-net-about-design-and-analysis-of-small-population-clinical-trials
#9
REVIEW
Ralf-Dieter Hilgers, Malgorzata Bogdan, Carl-Fredrik Burman, Holger Dette, Mats Karlsson, Franz König, Christoph Male, France Mentré, Geert Molenberghs, Stephen Senn
BACKGROUND: IDeAl (Integrated designs and analysis of small population clinical trials) is an EU funded project developing new statistical design and analysis methodologies for clinical trials in small population groups. Here we provide an overview of IDeAl findings and give recommendations to applied researchers. METHOD: The description of the findings is broken down by the nine scientific IDeAl work packages and summarizes results from the project's more than 60 publications to date in peer reviewed journals...
May 11, 2018: Orphanet Journal of Rare Diseases
https://www.readbyqxmd.com/read/29750165/how-artificial-intelligence-can-improve-our-understanding-of-the-genes-associated-with-endometriosis-natural-language-processing-of-the-pubmed-database
#10
REVIEW
J Bouaziz, R Mashiach, S Cohen, A Kedem, A Baron, M Zajicek, I Feldman, D Seidman, D Soriano
Endometriosis is a disease characterized by the development of endometrial tissue outside the uterus, but its cause remains largely unknown. Numerous genes have been studied and proposed to help explain its pathogenesis. However, the large number of these candidate genes has made functional validation through experimental methodologies nearly impossible. Computational methods could provide a useful alternative for prioritizing those most likely to be susceptibility genes. Using artificial intelligence applied to text mining, this study analyzed the genes involved in the pathogenesis, development, and progression of endometriosis...
2018: BioMed Research International
https://www.readbyqxmd.com/read/29749833/neurotransmitter-receptor-genotypes-associated-with-mental-and-behavioral-disorders
#11
Ekrem Varoglu, Adil Seytanoglu, Esra Asilmaz, Bahar Taneri
AIM: Investigation of association studies within the field of mental and behavioral disorders is of value given their complex molecular etiology including epistatic interactions of multiple genes with small effects. MATERIALS & METHODS: Utilizing biomedical text mining, associations are uncovered for all mental and behavioral conditions listed in Diagnostic and Statistical Manual of Mental Disorders Text Revision. Specifically, a computational pipeline is designed to retrieve neurotransmitter receptor variations from biomedical literature with a text mining approach, where unique polymorphisms are also mined...
July 2017: Personalized Medicine
https://www.readbyqxmd.com/read/29746916/an-effective-neural-model-extracting-document-level-chemical-induced-disease-relations-from-biomedical-literature
#12
Wei Zheng, Hongfei Lin, Zhiheng Li, Xiaoxia Liu, Zhengguang Li, Bo Xu, Yijia Zhang, Zhihao Yang, Jian Wang
Since identifying relations between chemicals and diseases (CDR) are important for biomedical research and healthcare, the challenge proposed by BioCreative V requires automatically mining causal relationships between chemicals and diseases which may span sentence boundaries. Although most systems explore feature engineering and knowledge bases to recognize document level CDR relations, feature learning automatically is limited only in a sentence. In this work, we proposed an effective model that automatically learns document level semantic representations to extract chemical-induced disease (CID) relations from articles by combining advantages of convolutional neural network and recurrent neural network...
May 7, 2018: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/29743155/causality-patterns-for-detecting-adverse-drug-reactions-from-social-media-text-mining-approach
#13
Danushka Bollegala, Simon Maskell, Richard Sloane, Joanna Hajne, Munir Pirmohamed
BACKGROUND: Detecting adverse drug reactions (ADRs) is an important task that has direct implications for the use of that drug. If we can detect previously unknown ADRs as quickly as possible, then this information can be provided to the regulators, pharmaceutical companies, and health care organizations, thereby potentially reducing drug-related morbidity and saving lives of many patients. A promising approach for detecting ADRs is to use social media platforms such as Twitter and Facebook...
May 9, 2018: JMIR Public Health and Surveillance
https://www.readbyqxmd.com/read/29742572/development-of-human-face-literature-database-using-text-mining-approach-phase-i
#14
Paramjit Kaur, Kewal Krishan, Suresh K Sharma
The face is an important part of the human body by which an individual communicates in the society. Its importance can be highlighted by the fact that a person deprived of face cannot sustain in the living world. The amount of experiments being performed and the number of research papers being published under the domain of human face have surged in the past few decades. Several scientific disciplines, which are conducting research on human face include: Medical Science, Anthropology, Information Technology (Biometrics, Robotics, and Artificial Intelligence, etc...
May 8, 2018: Journal of Craniofacial Surgery
https://www.readbyqxmd.com/read/29734478/text-mining-as-a-methodology-to-assess-eating-disorder-relevant-factors-comparing-mentions-of-fitness-tracking-technology-across-online-communities
#15
Duncan McCaig, Sudeep Bhatia, Mark T Elliott, Lukasz Walasek, Caroline Meyer
OBJECTIVE: Text-mining offers a technique to identify and extract information from a large corpus of textual data. As an example, this study presents the application of text-mining to assess and compare interest in fitness tracking technology across eating disorder and health-related online communities. METHOD: A list of fitness tracking technology terms was developed, and communities (i.e., 'subreddits') on a large online discussion platform (Reddit) were compared regarding the frequency with which these terms occurred...
May 7, 2018: International Journal of Eating Disorders
https://www.readbyqxmd.com/read/29728344/trends-in-hiv-terminology-text-mining-and-data-visualization-assessment-of-international-aids-conference-abstracts-over-25-years
#16
Nicole Dancy-Scott, Gale A Dutcher, Alla Keselman, Colette Hochstein, Christina Copty, Diane Ben-Senia, Sampada Rajan, Maria Guadalupe Asencio, Jason Jongwon Choi
BACKGROUND: The language encompassing health conditions can also influence behaviors that affect health outcomes. Few published quantitative studies have been conducted that evaluate HIV-related terminology changes over time. To expand this research, this study included an analysis of a dataset of abstracts presented at the International AIDS Conference (IAC) from 1989 to 2014. These abstracts reflect the global response to HIV over 25 years. Two powerful methodologies were used to evaluate the dataset: text mining to convert the unstructured information into structured data for analysis and data visualization to represent the data visually to assess trends...
May 4, 2018: JMIR Public Health and Surveillance
https://www.readbyqxmd.com/read/29728247/mining-protein-phosphorylation-information-from-biomedical-literature-using-nlp-parsing-and-support-vector-machines
#17
Kalpana Raja, Jeyakumar Natarajan
BACKGROUND: Extraction of protein phosphorylation information from biomedical literature has gained much attention because of the importance in numerous biological processes. OBJECTIVE: In this study, we propose a text mining methodology which consists of two phases, NLP parsing and SVM classification to extract phosphorylation information from literature. METHODS: First, using NLP parsing we divide the data into three base-forms depending on the biomedical entities related to phosphorylation and further classify into ten sub-forms based on their distribution with phosphorylation keyword...
July 2018: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/29727278/clinical-report-guided-retinal-microaneurysm-detection-with-multi-sieving-deep-learning
#18
Ling Dai, Ruogu Fang, Huating Li, Xuhong Hou, Bin Sheng, Qiang Wu, Weiping Jia
Timely detection and treatment of microaneurysms is a critical step to prevent the development of vision-threatening eye diseases such as diabetic retinopathy. However, detecting microaneurysms in fundus images is a highly challenging task due to the low image contrast, misleading cues of other red lesions, and the large variation of imaging conditions. Existing methods tend to fail in face of the large intra-class variation and small inter-class variations for microaneurysm detection in fundus images. Recently, hybrid text/image mining computer-aided diagnosis systems have emerged to offer a promise of bridging the semantic gap between images and diagnostic information...
May 2018: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/29726450/towards-phenotyping-of-clinical-trial-eligibility-criteria
#19
Matthias Löbe, Sebastian Stäubert, Colleen Goldberg, Ivonne Haffner, Alfred Winter
BACKGROUND: Medical plaintext documents contain important facts about patients, but they are rarely available for structured queries. The provision of structured information from natural language texts in addition to the existing structured data can significantly speed up the search for fulfilled inclusion criteria and thus improve the recruitment rate. OBJECTIVES: This work is aimed at supporting clinical trial recruitment with text mining techniques to identify suitable subjects in hospitals...
2018: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/29716399/informed-consent-in-pediatric-oncology-a-systematic-review-of-qualitative-literature
#20
Ghiath Alahmad
OBJECTIVE: Obtaining informed consent in pediatric cancer research can be subject to important ethical challenges because of the difficulty in distinguishing between care and research, which are interrelated. Pediatric oncologists also often conduct research, such as clinical trials, on their own patients, which may influence voluntary informed consent. This review aims to determine the ethical issues encountered in obtaining informed consent in pediatric oncology by identifying and summarizing the findings of existing qualitative studies on this topic...
January 2018: Cancer Control: Journal of the Moffitt Cancer Center
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