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"Natural Language Processing"

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https://www.readbyqxmd.com/read/29782036/differential-diagnosis-of-jaw-pain-using-informatics-technology
#1
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/29771635/pathogenesis-based-treatments-in-primary-sjogren-s-syndrome-using-artificial-intelligence-and-advanced-machine-learning-techniques-a-systematic-literature-review
#2
Nathan Foulquier, Pascal Redou, Christophe Le Gal, Bénédicte Rouvière, Jacques-Olivier Pers, Alain Saraux
Big data analysis has become a common way to extract information from complex and large datasets among most scientific domains. This approach is now used to study large cohorts of patients in medicine. This work is a review of publications that have used artificial intelligence and advanced machine learning techniques to study physio pathogenesis-based treatments in pSS. A systematic literature review retrieved all articles reporting on the use of advanced statistical analysis applied to the study of systemic autoimmune diseases (SADs) over the last decade...
May 17, 2018: Human Vaccines & Immunotherapeutics
https://www.readbyqxmd.com/read/29764360/prediction-of-enhancer-promoter-interactions-via-natural-language-processing
#3
Wanwen Zeng, Mengmeng Wu, Rui Jiang
BACKGROUND: Precise identification of three-dimensional genome organization, especially enhancer-promoter interactions (EPIs), is important to deciphering gene regulation, cell differentiation and disease mechanisms. Currently, it is a challenging task to distinguish true interactions from other nearby non-interacting ones since the power of traditional experimental methods is limited due to low resolution or low throughput. RESULTS: We propose a novel computational framework EP2vec to assay three-dimensional genomic interactions...
May 9, 2018: BMC Genomics
https://www.readbyqxmd.com/read/29763706/exploiting-semantic-patterns-over-biomedical-knowledge-graphs-for-predicting-treatment-and-causative-relations
#4
Gokhan Bakal, Preetham Talari, Elijah V Kakani, Ramakanth Kavuluru
BACKGROUND: Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches are first attempted to identify promising candidates. Likewise, identifying different causal relations between biomedical entities is also critical to understand biomedical processes. Generally, natural language processing (NLP) and machine learning are used to predict specific relations between any given pair of entities using the distant supervision approach...
May 12, 2018: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/29760666/candyflipping-and-other-combinations-identifying-drug-drug-combinations-from-an-online-forum
#5
Michael Chary, David Yi, Alex F Manini
Novel psychoactive substances (NPS) refer to synthetic compounds or derivatives of more widely known substances of abuse that have emerged over the last two decades. Case reports suggest that users combine substances to achieve desired psychotropic experiences while reducing dysphoria and unpleasant somatic effects. However, the pattern of combining NPS has not been studied on a large scale. Here, we show that posts discussing NPS describe combining nootropics with sedative-hypnotics and stimulants with plant hallucinogens or psychiatric medications...
2018: Frontiers in Psychiatry
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
#6
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/29743531/identifying-suicide-ideation-and-suicidal-attempts-in-a-psychiatric-clinical-research-database-using-natural-language-processing
#7
Andrea C Fernandes, Rina Dutta, Sumithra Velupillai, Jyoti Sanyal, Robert Stewart, David Chandran
Research into suicide prevention has been hampered by methodological limitations such as low sample size and recall bias. Recently, Natural Language Processing (NLP) strategies have been used with Electronic Health Records to increase information extraction from free text notes as well as structured fields concerning suicidality and this allows access to much larger cohorts than previously possible. This paper presents two novel NLP approaches - a rule-based approach to classify the presence of suicide ideation and a hybrid machine learning and rule-based approach to identify suicide attempts in a psychiatric clinical database...
May 9, 2018: Scientific Reports
https://www.readbyqxmd.com/read/29742757/evaluation-of-a-novel-system-to-enhance-clinicians-recognition-of-preadmission-adverse-drug-reactions
#8
Joshua C Smith, Qingxia Chen, Joshua C Denny, Dan M Roden, Kevin B Johnson, Randolph A Miller
BACKGROUND:  Often unrecognized by providers, adverse drug reactions (ADRs) diminish patients' quality of life, cause preventable admissions and emergency department visits, and increase health care costs. OBJECTIVE:  This article evaluates whether an automated system, the Adverse Drug Effect Recognizer (ADER), could assist clinicians in detecting and addressing inpatients' ongoing preadmission ADRs. METHODS:  ADER uses natural language processing to extract patients' medications, findings, and past diagnoses from admission notes...
April 2018: Applied Clinical Informatics
https://www.readbyqxmd.com/read/29732265/extraction-of-phenotypic-traits-from-taxonomic-descriptions-for-the-tree-of-life-using-natural-language-processing
#9
Lorena Endara, Hong Cui, J Gordon Burleigh
Premise of the Study: Phenotypic data sets are necessary to elucidate the genealogy of life, but assembling phenotypic data for taxa across the tree of life can be technically challenging and prohibitively time consuming. We describe a semi-automated protocol to facilitate and expedite the assembly of phenotypic character matrices of plants from formal taxonomic descriptions. This pipeline uses new natural language processing (NLP) techniques and a glossary of over 9000 botanical terms...
March 2018: Applications in Plant Sciences
https://www.readbyqxmd.com/read/29732166/secondary-use-of-electronic-medical-records-for-clinical-research-challenges-and-opportunities
#10
Wen-Wai Yim, Amanda J Wheeler, Catherine Curtin, Todd H Wagner, Tina Hernandez-Boussard
With increasingly ubiquitous electronic medical record (EMR) implementation accelerated by the adoption of the HITECH Act, there is much interest in the secondary use of collected data to improve outcomes and promote personalized medicine. A plethora of research has emerged using EMRs to investigate clinical research questions and assess variations in both treatments and outcomes. However, whether because of genuine complexities of modeling disease physiology or because of practical problems regarding data capture, data accuracy, and data completeness, the state of current EMR research is challenging and gives rise to concerns regarding study accuracy and reproducibility...
March 2018: Convergent Science Physical Oncology
https://www.readbyqxmd.com/read/29726425/ehr-text-categorization-for-enhanced-patient-based-document-navigation
#11
Markus Kreuzthaler, Bastian Pfeifer, José Antonio Vera Ramos, Diether Kramer, Victor Grogger, Sylvia Bredenfeldt, Markus Pedevilla, Peter Krisper, Stefan Schulz
Patients with multiple disorders usually have long diagnosis lists, constitute by ICD-10 codes together with individual free-text descriptions. These text snippets are produced by overwriting standardized ICD-Code topics by the physicians at the point of care. They provide highly compact expert descriptions within a 50-character long text field frequently not assigned to a specific ICD-10 code. The high redundancy of these lists would benefit from content-based categorization within different hospital-based application scenarios...
2018: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/29710833/social-sentiment-sensor-in-twitter-for-predicting-cyber-attacks-using-%C3%A2-%C3%A2-regularization
#12
Aldo Hernandez-Suarez, Gabriel Sanchez-Perez, Karina Toscano-Medina, Victor Martinez-Hernandez, Hector Perez-Meana, Jesus Olivares-Mercado, Victor Sanchez
In recent years, online social media information has been the subject of study in several data science fields due to its impact on users as a communication and expression channel. Data gathered from online platforms such as Twitter has the potential to facilitate research over social phenomena based on sentiment analysis, which usually employs Natural Language Processing and Machine Learning techniques to interpret sentimental tendencies related to users’ opinions and make predictions about real events...
April 29, 2018: Sensors
https://www.readbyqxmd.com/read/29707416/health-information-needs-and-health-seeking-behavior-during-the-2014-2016-ebola-outbreak-a-twitter-content-analysis
#13
Michelle Odlum, Sunmoo Yoon
Introduction: For effective public communication during major disease outbreaks like the 2014-2016 Ebola epidemic, health information needs of the population must be adequately assessed. Through content analysis of social media data, like tweets, public health information needs can be effectively assessed and in turn provide appropriate health information to address such needs. The aim of the current study was to assess health information needs about Ebola, at distinct epidemic time points, through longitudinal tracking...
March 23, 2018: PLoS Currents
https://www.readbyqxmd.com/read/29706858/matching-events-and-activities-by-integrating-behavioral-aspects-and-label-analysis
#14
Thomas Baier, Claudio Di Ciccio, Jan Mendling, Mathias Weske
Nowadays, business processes are increasingly supported by IT services that produce massive amounts of event data during the execution of a process. These event data can be used to analyze the process using process mining techniques to discover the real process, measure conformance to a given process model, or to enhance existing models with performance information. Mapping the produced events to activities of a given process model is essential for conformance checking, annotation and understanding of process mining results...
2018: Software and Systems Modeling
https://www.readbyqxmd.com/read/29705196/automatic-address-validation-and-health-record-review-to-identify-homeless-social-security-disability-applicants
#15
Jennifer Erickson, Kenneth Abbott, Lucinda Susienka
OBJECTIVE: Homeless patients face a variety of obstacles in pursuit of basic social services. Acknowledging this, the Social Security Administration directs employees to prioritize homeless patients and handle their disability claims with special care. However, under existing manual processes for identification of homelessness, many homeless patients never receive the special service to which they are entitled. In this paper, we explore address validation and automatic annotation of electronic health records to improve identification of homeless patients...
April 26, 2018: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/29696484/determining-post-test-risk-in-a-national-sample-of-stress-nuclear-myocardial-perfusion-imaging-reports-implications-for-natural-language-processing-tools
#16
Andrew E Levy, Nishant R Shah, Michael E Matheny, Ruth M Reeves, Glenn T Gobbel, Steven M Bradley
BACKGROUND: Reporting standards promote clarity and consistency of stress myocardial perfusion imaging (MPI) reports, but do not require an assessment of post-test risk. Natural Language Processing (NLP) tools could potentially help estimate this risk, yet it is unknown whether reports contain adequate descriptive data to use NLP. METHODS: Among VA patients who underwent stress MPI and coronary angiography between January 1, 2009 and December 31, 2011, 99 stress test reports were randomly selected for analysis...
April 25, 2018: Journal of Nuclear Cardiology: Official Publication of the American Society of Nuclear Cardiology
https://www.readbyqxmd.com/read/29696479/natural-language-processing-accurately-calculates-adenoma-and-sessile-serrated-polyp-detection-rates
#17
Jennifer Nayor, Lawrence F Borges, Sergey Goryachev, Vivian S Gainer, John R Saltzman
BACKGROUND: ADR is a widely used colonoscopy quality indicator. Calculation of ADR is labor-intensive and cumbersome using current electronic medical databases. Natural language processing (NLP) is a method used to extract meaning from unstructured or free text data. AIMS: (1) To develop and validate an accurate automated process for calculation of adenoma detection rate (ADR) and serrated polyp detection rate (SDR) on data stored in widely used electronic health record systems, specifically Epic electronic health record system, Provation® endoscopy reporting system, and Sunquest PowerPath pathology reporting system...
April 26, 2018: Digestive Diseases and Sciences
https://www.readbyqxmd.com/read/29695376/clinical-relation-extraction-toward-drug-safety-surveillance-using-electronic-health-record-narratives-classical-learning-versus-deep-learning
#18
Tsendsuren Munkhdalai, Feifan Liu, Hong Yu
BACKGROUND: Medication and adverse drug event (ADE) information extracted from electronic health record (EHR) notes can be a rich resource for drug safety surveillance. Existing observational studies have mainly relied on structured EHR data to obtain ADE information; however, ADEs are often buried in the EHR narratives and not recorded in structured data. OBJECTIVE: To unlock ADE-related information from EHR narratives, there is a need to extract relevant entities and identify relations among them...
April 25, 2018: JMIR Public Health and Surveillance
https://www.readbyqxmd.com/read/29689571/endoscopist-factors-that-influence-serrated-polyp-detection-a-multicenter-study
#19
Seth D Crockett, Rebecca A Gourevitch, Michele Morris, David S Carrell, Sherri Rose, Zhuo Shi, Julia B Greer, Robert E Schoen, Ateev Mehrotra
BACKGROUND:  Serrated polyps are important colorectal cancer precursors that are variably detected during colonoscopy. We measured serrated polyp detection rate (SPDR) in a large, multicenter, cross-sectional study of colonoscopy quality to identify drivers of SPDR variation. METHODS:  Colonoscopy and pathology reports were collected for a 2-year period (10/2013-9/2015) from four sites across the United States. Data from reports, including size, location, and histology of polyps, were abstracted using a validated natural language processing algorithm...
April 24, 2018: Endoscopy
https://www.readbyqxmd.com/read/29681027/terminology-services-standard-terminologies-to-control-health-vocabulary
#20
Fernán González Bernaldo de Quirós, Carlos Otero, Daniel Luna
Healthcare Information Systems should capture clinical data in a structured and preferably coded format. This is crucial for data exchange between health information systems, epidemiological analysis, quality and research, clinical decision support systems, administrative functions, among others. Structured data entry is an obstacle for the usability of electronic health record (EHR) applications and their acceptance by physicians who prefer to document patient EHRs using "free text". Natural language allows for rich expressiveness but at the same time is ambiguous; it has great dependence on context and uses jargon and acronyms...
April 22, 2018: Yearbook of Medical Informatics
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