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https://www.readbyqxmd.com/read/28723265/a-text-mining-analysis-of-the-public-s-reactions-to-the-opioid-crisis
#1
Elizabeth M Glowacki, Joseph B Glowacki, Gary B Wilcox
BACKGROUND: Opioid abuse has become an epidemic in the United States. On August 25, 2016, the former Surgeon General of the United States sent an open letter to care providers asking for their help with combatting this growing health crisis. Social media forums like Twitter allow for open discussions among the public and up-to-date exchanges of information about timely topics like opioids. Therefore, the goal of the current study is to identify the public's reactions to the opioid epidemic by identifying the most popular topics tweeted by users...
July 19, 2017: Substance Abuse
https://www.readbyqxmd.com/read/28715259/teaching-principal-components-using-correlations
#2
Peter H Westfall, Andrea L Arias, Larry V Fulton
Introducing principal components (PCs) to students is difficult. First, the matrix algebra and mathematical maximization lemmas are daunting, especially for students in the social and behavioral sciences. Second, the standard motivation involving variance maximization subject to unit length constraint does not directly connect to the "variance explained" interpretation. Third, the unit length and uncorrelatedness constraints of the standard motivation do not allow re-scaling or oblique rotations, which are common in practice...
July 17, 2017: Multivariate Behavioral Research
https://www.readbyqxmd.com/read/28715190/chemical-topic-modeling-exploring-molecular-datasets-using-a-common-text-mining-approach
#3
Nadine Schneider, Nikolas Fechner, Gregory A Landrum, Nikolaus Stiefl
Big data is one of the key transformative factors which are increasingly influencing all aspects of modern life. Although this transformation brings vast opportunities it also generates novel challenges, not the least of which is organizing and searching this data deluge. The field of medicinal chemistry is not different: more and more data are being generated, for instance by technologies such as DNA encoded libraries, peptide libraries, text mining of large literature corpora, and new in silico enumeration methods...
July 17, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28711679/reproducibility-of-studies-on-text-mining-for-citation-screening-in-systematic-reviews-evaluation-and-checklist
#4
Babatunde Kazeem Olorisade, Pearl Brereton, Peter Andras
CONTEXT: Independent validation of published scientific results through study replication is a pre-condition for accepting the validity of such results. In computation research, full replication is often unrealistic for independent results validation, therefore, study reproduction has been justified as the minimum acceptable standard to evaluate the validity of scientific claims. The application of text mining techniques to citation screening in the context of systematic literature reviews is a relatively young and growing computational field with high relevance for software engineering, medical research and other fields...
July 12, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28706471/scalable-text-mining-assisted-curation-of-post-translationally-modified-proteoforms-in-the-protein-ontology
#5
Karen E Ross, Darren A Natale, Cecilia Arighi, Sheng-Chih Chen, Hongzhan Huang, Gang Li, Jia Ren, Michael Wang, K Vijay-Shanker, Cathy H Wu
The Protein Ontology (PRO) defines protein classes and their interrelationships from the family to the protein form (proteoform) level within and across species. One of the unique contributions of PRO is its representation of post-translationally modified (PTM) proteoforms. However, progress in adding PTM proteoform classes to PRO has been relatively slow due to the extensive manual curation effort required. Here we report an automated pipeline for creation of PTM proteoform classes that leverages two phosphorylation-focused text mining tools (RLIMS-P, which detects mentions of kinases, substrates, and phosphorylation sites, and eFIP, which detects phosphorylation-dependent protein-protein interactions (PPIs)) and our integrated PTM database, iPTMnet...
August 2016: CEUR Workshop Proceedings
https://www.readbyqxmd.com/read/28694239/assessing-suicide-risk-and-emotional-distress-in-chinese-social-media-a-text-mining-and-machine-learning-study
#6
Qijin Cheng, Tim Mh Li, Chi-Leung Kwok, Tingshao Zhu, Paul Sf Yip
BACKGROUND: Early identification and intervention are imperative for suicide prevention. However, at-risk people often neither seek help nor take professional assessment. A tool to automatically assess their risk levels in natural settings can increase the opportunity for early intervention. OBJECTIVE: The aim of this study was to explore whether computerized language analysis methods can be utilized to assess one's suicide risk and emotional distress in Chinese social media...
July 10, 2017: Journal of Medical Internet Research
https://www.readbyqxmd.com/read/28692985/emdl-extracting-mirna-drug-interactions-from-literature
#7
Wenbin Xie, Hong Yan, Xing-Ming Zhao
The microRNAs (miRNAs), regulators of post-transcriptional processes, have been found to affect the efficacy of drugs by regulating the biological processes in which the target proteins of drugs may be involved. For example, some drugs develop resistance when certain miRNAs are overexpressed. Therefore, identifying miRNAs that affect drug effects can help understand the mechanisms of drug actions and design more efficient drugs. Although some computational approaches have been developed to predict miRNA-drug associations, such associations rarely provide explicit information about which miRNAs and how they affect drug efficacy...
July 6, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28688492/quantifying-the-informativeness-for-biomedical-literature-summarization-an-itemset-mining-method
#8
Milad Moradi, Nasser Ghadiri
OBJECTIVE: Automatic text summarization tools can help users in the biomedical domain to access information efficiently from a large volume of scientific literature and other sources of text documents. In this paper, we propose a summarization method that combines itemset mining and domain knowledge to construct a concept-based model and to extract the main subtopics from an input document. Our summarizer quantifies the informativeness of each sentence using the support values of itemsets appearing in the sentence...
July 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28678852/enriching-plausible-new-hypothesis-generation-in-pubmed
#9
Seung Han Baek, Dahee Lee, Minjoo Kim, Jong Ho Lee, Min Song
BACKGROUND: Most of earlier studies in the field of literature-based discovery have adopted Swanson's ABC model that links pieces of knowledge entailed in disjoint literatures. However, the issue concerning their practicability remains to be solved since most of them did not deal with the context surrounding the discovered associations and usually not accompanied with clinical confirmation. In this study, we aim to propose a method that expands and elaborates the existing hypothesis by advanced text mining techniques for capturing contexts...
2017: PloS One
https://www.readbyqxmd.com/read/28678823/assigning-factuality-values-to-semantic-relations-extracted-from-biomedical-research-literature
#10
Halil Kilicoglu, Graciela Rosemblat, Thomas C Rindflesch
Biomedical knowledge claims are often expressed as hypotheses, speculations, or opinions, rather than explicit facts (propositions). Much biomedical text mining has focused on extracting propositions from biomedical literature. One such system is SemRep, which extracts propositional content in the form of subject-predicate-object triples called predications. In this study, we investigated the feasibility of assessing the factuality level of SemRep predications to provide more nuanced distinctions between predications for downstream applications...
2017: PloS One
https://www.readbyqxmd.com/read/28678787/classification-and-analysis-of-a-large-collection-of-in-vivo-bioassay-descriptions
#11
Magdalena Zwierzyna, John P Overington
Testing potential drug treatments in animal disease models is a decisive step of all preclinical drug discovery programs. Yet, despite the importance of such experiments for translational medicine, there have been relatively few efforts to comprehensively and consistently analyze the data produced by in vivo bioassays. This is partly due to their complexity and lack of accepted reporting standards-publicly available animal screening data are only accessible in unstructured free-text format, which hinders computational analysis...
July 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28663166/researching-mental-health-disorders-in-the-era-of-social-media-systematic-review
#12
REVIEW
Akkapon Wongkoblap, Miguel A Vadillo, Vasa Curcin
BACKGROUND: Mental illness is quickly becoming one of the most prevalent public health problems worldwide. Social network platforms, where users can express their emotions, feelings, and thoughts, are a valuable source of data for researching mental health, and techniques based on machine learning are increasingly used for this purpose. OBJECTIVE: The objective of this review was to explore the scope and limits of cutting-edge techniques that researchers are using for predictive analytics in mental health and to review associated issues, such as ethical concerns, in this area of research...
June 29, 2017: Journal of Medical Internet Research
https://www.readbyqxmd.com/read/28663163/validation-of-an-improved-computer-assisted-technique-for-mining-free-text-electronic-medical-records
#13
Marco Duz, John F Marshall, Tim Parkin
BACKGROUND: The use of electronic medical records (EMRs) offers opportunity for clinical epidemiological research. With large EMR databases, automated analysis processes are necessary but require thorough validation before they can be routinely used. OBJECTIVE: The aim of this study was to validate a computer-assisted technique using commercially available content analysis software (SimStat-WordStat v.6 (SS/WS), Provalis Research) for mining free-text EMRs. METHODS: The dataset used for the validation process included life-long EMRs from 335 patients (17,563 rows of data), selected at random from a larger dataset (141,543 patients, ~2...
June 29, 2017: JMIR Medical Informatics
https://www.readbyqxmd.com/read/28660680/text-mining-for-search-term-development-in-systematic-reviewing-a-discussion-of-some-methods-and-challenges
#14
Claire Stansfield, Alison O'Mara-Eves, James Thomas
Using text mining to aid the development of database search strings for topics described by diverse terminology has potential benefits for systematic reviews; however, methods and tools for accomplishing this are poorly covered in the research methods literature. We briefly review the literature on applications of text mining for search term development for systematic reviewing. We found that the tools can be used in 5 overarching ways: improving the precision of searches; identifying search terms to improve search sensitivity; aiding the translation of search strategies across databases; searching and screening within an integrated system; and developing objectively derived search strategies...
June 29, 2017: Research Synthesis Methods
https://www.readbyqxmd.com/read/28652513/study-on-students-impression-data-in-practical-training-using-text-mining-method-analysis-of-considerable-communication
#15
Hitomi Teramachi, Ikuto Sugita, Yoko Ino, Yuta Hayashi, Aki Yoshida, Manami Otsubo, Anri Ueno, Hayato Katsuno, Yoshihiro Noguchi, Kazuhiro Iguchi, Tomoya Tachi
  We analyzed impression data and the scale of communication skills of students using text mining method to clarify which area a student was conscious of in communication in practical training. The results revealed that students tended to be conscious of the difference between practical hospital training and practical pharmacy training. In practical hospital training, specific expressions denoting relationships were "patient-visit", "counseling-conduct", "patient-counseling", and "patient-talk". In practical pharmacy training, specific expressions denoting relationships were "patient counseling-conduct", "story-listen", "patient-many", and "patient-visit"...
June 26, 2017: Yakugaku Zasshi: Journal of the Pharmaceutical Society of Japan
https://www.readbyqxmd.com/read/28651340/linking-quality-indicators-to-clinical-trials-an-automated-approach
#16
Enrico Coiera, Miew Keen Choong, Guy Tsafnat, Peter Hibbert, William B Runciman
Objective: Quality improvement of health care requires robust measurable indicators to track performance. However identifying which indicators are supported by strong clinical evidence, typically from clinical trials, is often laborious. This study tests a novel method for automatically linking indicators to clinical trial registrations. Design: A set of 522 quality of care indicators for 22 common conditions drawn from the CareTrack study were automatically mapped to outcome measures reported in 13 971 trials from ClinicalTrials...
June 23, 2017: International Journal for Quality in Health Care
https://www.readbyqxmd.com/read/28644851/comorbidities-in-the-diseasome-are-more-apparent-than-real-what-bayesian-filtering-reveals-about-the-comorbidities-of-depression
#17
Peter Marx, Peter Antal, Bence Bolgar, Gyorgy Bagdy, Bill Deakin, Gabriella Juhasz
Comorbidity patterns have become a major source of information to explore shared mechanisms of pathogenesis between disorders. In hypothesis-free exploration of comorbid conditions, disease-disease networks are usually identified by pairwise methods. However, interpretation of the results is hindered by several confounders. In particular a very large number of pairwise associations can arise indirectly through other comorbidity associations and they increase exponentially with the increasing breadth of the investigated diseases...
June 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28633401/biomedical-text-mining-for-research-rigor-and-integrity-tasks-challenges-directions
#18
Halil Kilicoglu
An estimated quarter of a trillion US dollars is invested in the biomedical research enterprise annually. There is growing alarm that a significant portion of this investment is wasted because of problems in reproducibility of research findings and in the rigor and integrity of research conduct and reporting. Recent years have seen a flurry of activities focusing on standardization and guideline development to enhance the reproducibility and rigor of biomedical research. Research activity is primarily communicated via textual artifacts, ranging from grant applications to journal publications...
June 13, 2017: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/28624641/text-mining-applied-to-electronic-cardiovascular-procedure-reports-to-identify-patients-with-trileaflet-aortic-stenosis-and-coronary-artery-disease
#19
Aeron M Small, Daniel H Kiss, Yevgeny Zlatsin, David L Birtwell, Heather Williams, Marie A Guerraty, Yuchi Han, Saif Anwaruddin, John H Holmes, Julio A Chirinos, Robert L Wilensky, Jay Giri, Daniel J Rader
BACKGROUND: Interrogation of the electronic health record (EHR) using billing codes as a surrogate for diagnoses of interest has been widely used for clinical research. However, the accuracy of this methodology is variable, as it reflects billing codes rather than severity of disease, and depends on the disease and the accuracy of the coding practitioner. Systematic application of text mining to the EHR has had variable success for the detection of cardiovascular phenotypes. We hypothesize that the application of text mining algorithms to cardiovascular procedure reports may be a superior method to identify patients with cardiovascular conditions of interest...
June 14, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28622674/a-two-stage-biomedical-event-trigger-detection-method-integrating-feature-selection-and-word-embeddings
#20
Xinyu He, Lishuang Li, Yang Liu, XiaoMing Yu, Jun Meng
Extracting biomedical events from biomedical literature plays an important role in the field of biomedical text mining, and the trigger detection is a key step in biomedical event extraction. We propose a two-stage method for trigger detection, which divides trigger detection into recognition stage and classification stage, and different features are selected in each stage. In the first stage, we select the features which are more suitable for recognition, and in the second stage, the features that are more helpful to classification are adopted...
June 13, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
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