1. 49-72 of 2811 « 1 2 3 4 5 6 ... 116 117 118 »
    1. Decoding naturalistic experiences from human brain activity via distributed representations of words.

      Decoding naturalistic experiences from human brain activity via distributed representations of words.

      Decoding naturalistic experiences from human brain activity via distributed representations of words.

      Neuroimage. 2017 Aug 08;:

      Authors: Nishida S, Nishimoto S

      Abstract Natural visual scenes induce rich perceptual experiences that are highly diverse from scene to scene and from person to person. Here, we propose a new framework for decoding such experiences using a distributed representation of words.

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    2. Automated Cancer Registry Notifications: Validation of a Medical Text Analytics System for Identifying Patients with Cancer from a State-Wide Pathology Repository.

      Automated Cancer Registry Notifications: Validation of a Medical Text Analytics System for Identifying Patients with Cancer from a State-Wide Pathology Repository.

      AMIA Annu Symp Proc. 2016;2016:964-973

      Authors: Nguyen AN, Moore J, O'Dwyer J, Philpot S

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    3. Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets.

      Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets.

      Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets.

      Elife. 2017 Aug 08;6:

      Authors: Maciejewski M, Lounkine E, Whitebread S, Farmer P, DuMouchel W, Shoichet BK, Urban L

      Abstract The Food and Drug Administration Adverse Event Reporting System (FAERS) remains the primary source for post-marketing pharmacovigilance.

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    4. Combining Open-domain and Biomedical Knowledge for Topic Recognition in Consumer Health Questions.

      Combining Open-domain and Biomedical Knowledge for Topic Recognition in Consumer Health Questions.

      Combining Open-domain and Biomedical Knowledge for Topic Recognition in Consumer Health Questions.

      AMIA Annu Symp Proc. 2016;2016:914-923

      Authors: Mrabet Y, Kilicoglu H, Roberts K, Demner-Fushman D

      Abstract Determining the main topics in consumer health questions is a crucial step in their processing as it allows narrowing the search space to a specific semantic context. In this paper we propose a topic recognition approach based on biomedical and open-domain knowledge bases.

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    5. Identification of people with acquired hemophilia in a large electronic health record database.

      Identification of people with acquired hemophilia in a large electronic health record database.

      Identification of people with acquired hemophilia in a large electronic health record database.

      J Blood Med. 2017;8:89-97

      Authors: Wang M, Cyhaniuk A, Cooper DL, Iyer NN

      Abstract BACKGROUND: Electronic health records (EHRs) can provide insights into diagnoses, treatment patterns, and clinical outcomes. Acquired hemophilia (AH) is an ultrarare bleeding disorder characterized by factor VIII inhibiting autoantibodies. AIM: To identify patients with AH using an EHR database.

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    6. Childhood respiratory illness presentation and service utilisation in primary care: a six-year cohort study in Wellington, New Zealand, using natural language processing (NLP) software.

      Childhood respiratory illness presentation and service utilisation in primary care: a six-year cohort study in Wellington, New Zealand, using natural language processing (NLP) software.

      Childhood respiratory illness presentation and service utilisation in primary care: a six-year cohort study in Wellington, New Zealand, using natural language processing (NLP) software.

      BMJ Open. 2017 Aug 01;7(7):e017146

      Authors: Dowell A, Darlow B, Macrae J, Stubbe M, Turner N, McBain L

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    7. a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.

      a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.

      TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.

      Sci Rep. 2017 Jul 31;7(1):6918

      Authors: Lin FP, Pokorny A, Teng C, Epstein RJ

      Abstract Vast amounts of clinically relevant text-based variables lie undiscovered and unexploited in electronic medical records (EMR).

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      Mentions: NLP ROC
    8. Triaging Patient Complaints: Monte Carlo Cross-Validation of Six Machine Learning Classifiers.

      Triaging Patient Complaints: Monte Carlo Cross-Validation of Six Machine Learning Classifiers.

      Triaging Patient Complaints: Monte Carlo Cross-Validation of Six Machine Learning Classifiers.

      JMIR Med Inform. 2017 Jul 31;5(3):e19

      Authors: Elmessiry A, Cooper WO, Catron TF, Karrass J, Zhang Z, Singh MP

      Abstract BACKGROUND: Unsolicited patient complaints can be a useful service recovery tool for health care organizations. Some patient complaints contain information that may necessitate further action on the part of the health care organization and/or the health care professional.

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    9. "What else are you worried about?" - Integrating textual responses into quantitative social science research.

      "What else are you worried about?" - Integrating textual responses into quantitative social science research.

      "What else are you worried about?" - Integrating textual responses into quantitative social science research.

      PLoS One. 2017;12(7):e0182156

      Authors: Rohrer JM, Brümmer M, Schmukle SC, Goebel J, Wagner GG

      Abstract Open-ended questions have routinely been included in large-scale survey and panel studies, yet there is some perplexity about how to actually incorporate the answers to such questions into quantitative social science research.

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    10. A Cascaded Approach for Chinese Clinical Text De-Identification with Less Annotation Effort.

      A Cascaded Approach for Chinese Clinical Text De-Identification with Less Annotation Effort.

      A Cascaded Approach for Chinese Clinical Text De-Identification with Less Annotation Effort.

      J Biomed Inform. 2017 Jul 26;:

      Authors: Jian Z, Guo X, Liu S, Ma H, Zhang S, Zhang R, Lei J

      Abstract With rapid adoption of Electronic Health Records (EHR) in China, an increasing amount of clinical data has been available to support clinical research. Clinical data secondary use usually requires de-identification of personal information to protect patient privacy.

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    11. SETH detects and normalizes genetic variants in text.

      SETH detects and normalizes genetic variants in text.

      SETH detects and normalizes genetic variants in text.

      Bioinformatics. 2016 Sep 15;32(18):2883-5

      Authors: Thomas P, Rocktäschel T, Hakenberg J, Lichtblau Y, Leser U

      Abstract UNLABELLED: : Descriptions of genetic variations and their effect are widely spread across the biomedical literature. However, finding all mentions of a specific variation, or all mentions of variations in a specific gene, is difficult to achieve due to the many ways such variations are described.

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      Mentions: Hakenberg J
    12. Knowledge Representation and Management. From Ontology to Annotation. Findings from the Yearbook 2015 Section on Knowledge Representation and Management.

      Knowledge Representation and Management. From Ontology to Annotation. Findings from the Yearbook 2015 Section on Knowledge Representation and Management.

      Knowledge Representation and Management. From Ontology to Annotation. Findings from the Yearbook 2015 Section on Knowledge Representation and Management.

      Yearb Med Inform. 2015 Aug 13;10(1):134-6

      Authors: Charlet J, Darmoni SJ

      Abstract OBJECTIVE: To summarize the best papers in the field of Knowledge Representation and Management (KRM). METHODS: A comprehensive review of medical informatics literature was performed to select some of the most interesting papers of KRM published in 2014.

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    13. Automated problem list generation and physicians perspective from a pilot study.

      Automated problem list generation and physicians perspective from a pilot study.

      Automated problem list generation and physicians perspective from a pilot study.

      Int J Med Inform. 2017 Sep;105:121-129

      Authors: Devarakonda MV, Mehta N, Tsou CH, Liang JJ, Nowacki AS, Jelovsek JE

      Abstract OBJECTIVE: An accurate, comprehensive and up-to-date problem list can help clinicians provide patient-centered care. Unfortunately, problem lists created and maintained in electronic health records by providers tend to be inaccurate, duplicative and out of date.

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      Mentions: EHR
    14. A comparison of rule-based and machine learning approaches for classifying patient portal messages.

      A comparison of rule-based and machine learning approaches for classifying patient portal messages.

      A comparison of rule-based and machine learning approaches for classifying patient portal messages.

      Int J Med Inform. 2017 Sep;105:110-120

      Authors: Cronin RM, Fabbri D, Denny JC, Rosenbloom ST, Jackson GP

      Abstract OBJECTIVE: Secure messaging through patient portals is an increasingly popular way that consumers interact with healthcare providers. The increasing burden of secure messaging can affect clinic staffing and workflows.

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    15. Continued Statin Prescriptions After Adverse Reactions and Patient Outcomes: A Cohort Study.

      Continued Statin Prescriptions After Adverse Reactions and Patient Outcomes: A Cohort Study.

      Continued Statin Prescriptions After Adverse Reactions and Patient Outcomes: A Cohort Study.

      Ann Intern Med. 2017 Jul 25;:

      Authors: Zhang H, Plutzky J, Shubina M, Turchin A

      Abstract Background: Many patients discontinue statin treatment, often after having a possible adverse reaction. The risks and benefits of continued statin therapy after an adverse reaction are not known.

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    16. Significant Linkage Evidence for Interstitial Cystitis/Painful Bladder Syndrome on Chromosome 3.

      Significant Linkage Evidence for Interstitial Cystitis/Painful Bladder Syndrome on Chromosome 3.

      Significant Linkage Evidence for Interstitial Cystitis/Painful Bladder Syndrome on Chromosome 3.

      J Urol. 2017 Jul 19;:

      Authors: Allen-Brady K, Rowe K, Cessna M, Lenherr S, Norton P

      Abstract PURPOSE: Interstitial cystitis/painful bladder syndrome (IC/PBS) is a chronic pelvic pain condition with unknown etiology. We hypothesized that related IC/PBS cases were more likely to have a genetic etiology. The purpose of this study was to perform a genetic linkage analysis.

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    17. Identification of the delivery of cognitive behavioural therapy for psychosis (CBTp) using a cross-sectional sample from electronic health records and open-text information in a large UK-based mental health case register.

      Identification of the delivery of cognitive behavioural therapy for psychosis (CBTp) using a cross-sectional sample from electronic health records and open-text information in a large UK-based mental health case register.

      Identification of the delivery of cognitive behavioural therapy for psychosis (CBTp) using a cross-sectional sample from electronic health records and open-text information in a large UK-based mental health case register.

      BMJ Open. 2017 Jul 17;7(7):e015297

      Authors: Colling C, Evans L, Broadbent M, Chandran D, Craig TJ, Kolliakou A, Stewart R, Garety PA

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    18. Feasibility of Automating Patient Acuity Measurement Using a Machine Learning Algorithm.

      Feasibility of Automating Patient Acuity Measurement Using a Machine Learning Algorithm.

      Feasibility of Automating Patient Acuity Measurement Using a Machine Learning Algorithm.

      J Nurs Meas. 2016 Dec 01;24(3):419-427

      Authors: Brennan CW, Meng F, Meterko MM, D'Avolio LW

      Abstract BACKGROUND AND PURPOSE: One method of determining nurse staffing is to match patient demand for nursing care (patient acuity) with available nursing staff. This pilot study explored the feasibility of automating acuity measurement using a machine learning algorithm.

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    19. Automatic Generation of Conditional Diagnostic Guidelines.

      Automatic Generation of Conditional Diagnostic Guidelines.

      AMIA Annu Symp Proc. 2016;2016:295-304

      Authors: Baldwin T, Guo Y, Syeda-Mahmood T

      Abstract The diagnostic workup for many diseases can be extraordinarily nuanced, and as such reference material text often contains extensive information regarding when it is appropriate to have a patient undergo a given procedure.

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    20. Estimating the average need of semantic knowledge from distributional semantic models.

      Estimating the average need of semantic knowledge from distributional semantic models.

      Estimating the average need of semantic knowledge from distributional semantic models.

      Mem Cognit. 2017 Jul 13;:

      Authors: Hollis G

      Abstract Continuous bag of words (CBOW) and skip-gram are two recently developed models of lexical semantics (Mikolov, Chen, Corrado, & Dean, Advances in Neural Information Processing Systems, 26, 3111-3119, 2013).

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    49-72 of 2811 « 1 2 3 4 5 6 ... 116 117 118 »
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD