1. 73-96 of 2862 « 1 2 3 4 5 6 7 ... 118 119 120 »
    1. Demystifying Multi-Task Deep Neural Networks for Quantitative Structure-Activity Relationships.

      Demystifying Multi-Task Deep Neural Networks for Quantitative Structure-Activity Relationships.

      Demystifying Multi-Task Deep Neural Networks for Quantitative Structure-Activity Relationships.

      J Chem Inf Model. 2017 Sep 05;:

      Authors: Xu Y, Ma J, Liaw A, Sheridan RP, Svetnik V

      Abstract Deep neural networks (DNNs) are complex computational models that have found great success in many artificial intelligence applications, such as computer vision and natural language processing.

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    2. Effects of non-medical switching on outcomes among patients prescribed tumor necrosis factor inhibitors.

      Effects of non-medical switching on outcomes among patients prescribed tumor necrosis factor inhibitors.

      Effects of non-medical switching on outcomes among patients prescribed tumor necrosis factor inhibitors.

      Curr Med Res Opin. 2017 Sep 05;:1-27

      Authors: Gibofsky A, Skup M, Mittal M, Johnson SJ, Davis M, Chao J, Rubin DT

      Abstract OBJECTIVE: To evaluate health care use and outcomes among patients who experienced a non-medical switch of their prescribed anti-tumor necrosis factor biological agent (anti-TNF) for cost containment reasons.

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    3. Using Naïve Bayesian Analysis to Determine Imaging Characteristics of KRAS Mutations in Metastatic Colon Cancer.

      Using Naïve Bayesian Analysis to Determine Imaging Characteristics of KRAS Mutations in Metastatic Colon Cancer.

      Using Naïve Bayesian Analysis to Determine Imaging Characteristics of KRAS Mutations in Metastatic Colon Cancer.

      Diagnostics (Basel). 2017 Sep 02;7(3):

      Authors: Pershad Y, Govindan S, Hara AK, Borad MJ, Bekaii-Saab T, Wallace A, Albadawi H, Oklu R

      Abstract Genotype, particularly Ras status, greatly affects prognosis and treatment of liver metastasis in colon cancer patients.

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      Mentions: Basel Bayes RAS
    4. Visual Exploration of Semantic Relationships in Neural Word Embeddings.

      Visual Exploration of Semantic Relationships in Neural Word Embeddings.

      Visual Exploration of Semantic Relationships in Neural Word Embeddings.

      IEEE Trans Vis Comput Graph. 2017 Aug 29;:

      Authors: Liu S, Bremer PT, Thiagarajan JJ, Srikumar V, Wang B, Livnat Y, Pascucci V

      Abstract Constructing distributed representations for words through neural language models and using the resulting vector spaces for analysis has become a crucial component of natural language processing (NLP).

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      Mentions: NLP PCA
    5. Physician Characteristics Associated with Higher Adenoma Detection Rate.

      Physician Characteristics Associated with Higher Adenoma Detection Rate.

      Physician Characteristics Associated with Higher Adenoma Detection Rate.

      Gastrointest Endosc. 2017 Aug 30;:

      Authors: Mehrotra A, Morris M, Gourevitch RA, Carrell DS, Leffler DA, Rose S, Greer JB, Crockett SD, Baer A, Schoen RE

      Abstract BACKGROUND & AIMS: Patients who receive a colonoscopy from a physician with a low adenoma detection rate are at higher risk of subsequent colorectal cancer. It is unclear what drives the variation across physicians in adenoma detection rate.

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    6. Accurate Identification of Fatty Liver Disease in Data Warehouse Utilizing Natural Language Processing.

      Accurate Identification of Fatty Liver Disease in Data Warehouse Utilizing Natural Language Processing.

      Accurate Identification of Fatty Liver Disease in Data Warehouse Utilizing Natural Language Processing.

      Dig Dis Sci. 2017 Aug 31;:

      Authors: Redman JS, Natarajan Y, Hou JK, Wang J, Hanif M, Feng H, Kramer JR, Desiderio R, Xu H, El-Serag HB, Kanwal F

      Abstract INTRODUCTION: Natural language processing is a powerful technique of machine learning capable of maximizing data extraction from complex electronic medical records.

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      Mentions: Xu H
    7. Comparison of Methods To Identify Advance Care Planning in Patients with Severe Chronic Obstructive Pulmonary Disease Exacerbation.

      Comparison of Methods To Identify Advance Care Planning in Patients with Severe Chronic Obstructive Pulmonary Disease Exacerbation.

      Comparison of Methods To Identify Advance Care Planning in Patients with Severe Chronic Obstructive Pulmonary Disease Exacerbation.

      J Palliat Med. 2017 Aug 29;:

      Authors: Stephens AR, Wiener RS, Ieong MH

      Abstract BACKGROUND: Advance care planning (ACP) is recommended for patients with chronic obstructive pulmonary disease (COPD).

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      Mentions: EMR ACP
    8. Downregulation of miR‑136‑5p in hepatocellular carcinoma and its clinicopathological significance.

      Downregulation of miR‑136‑5p in hepatocellular carcinoma and its clinicopathological significance.

      Downregulation of miR‑136‑5p in hepatocellular carcinoma and its clinicopathological significance.

      Mol Med Rep. 2017 Aug 17;:

      Authors: Ding H, Ye ZH, Wen DY, Huang XL, Zeng CM, Mo J, Jiang YQ, Li JJ, Cai XY, Yang H, Chen G

      Abstract The clinical significance of microRNA (miR)‑136‑5p in hepatocellular carcinoma (HCC) has not been verified.

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      Mentions: Yang H NLP Kegg
    9. Informatics Support for Basic Research in Biomedicine.

      Informatics Support for Basic Research in Biomedicine.

      Informatics Support for Basic Research in Biomedicine.

      ILAR J. 2017 Jul 01;58(1):80-89

      Authors: Rindflesch TC, Blake CL, Fiszman M, Kilicoglu H, Rosemblat G, Schneider J, Zeiss CJ

      Abstract Informatics methodologies exploit computer-assisted techniques to help biomedical researchers manage large amounts of information. In this paper, we focus on the biomedical research literature (MEDLINE).

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    10. Semantic Role Labeling of Clinical Text: Comparing Syntactic Parsers and Features.

      Semantic Role Labeling of Clinical Text: Comparing Syntactic Parsers and Features.

      AMIA Annu Symp Proc. 2016;2016:1283-1292

      Authors: Zhang Y, Jiang M, Wang J, Xu H

      Abstract Semantic role labeling (SRL), which extracts shallow semantic relation representation from different surface textual forms of free text sentences, is important for understanding clinical narratives.

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    11. Epidemiology from Tweets: Estimating Misuse of Prescription Opioids in the USA from Social Media.

      Epidemiology from Tweets: Estimating Misuse of Prescription Opioids in the USA from Social Media.

      Epidemiology from Tweets: Estimating Misuse of Prescription Opioids in the USA from Social Media.

      J Med Toxicol. 2017 Aug 22;:

      Authors: Chary M, Genes N, Giraud-Carrier C, Hanson C, Nelson LS, Manini AF

      Abstract BACKGROUND: The misuse of prescription opioids (MUPO) is a leading public health concern. Social media are playing an expanded role in public health research, but there are few methods for estimating established epidemiological metrics from social media.

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      Mentions: Social Media USA
    12. Word2Vec inversion and traditional text classifiers for phenotyping lupus.

      Word2Vec inversion and traditional text classifiers for phenotyping lupus.

      Word2Vec inversion and traditional text classifiers for phenotyping lupus.

      BMC Med Inform Decis Mak. 2017 Aug 22;17(1):126

      Authors: Turner CA, Jacobs AD, Marques CK, Oates JC, Kamen DL, Anderson PE, Obeid JS

      Abstract BACKGROUND: Identifying patients with certain clinical criteria based on manual chart review of doctors' notes is a daunting task given the massive amounts of text notes in the electronic health records (EHR).

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    13. Serious Choices: A Protocol for an Environmental Scan of Patient Decision Aids for Seriously Ill People at Risk of Death Facing Choices about Life-Sustaining Treatments.

      Serious Choices: A Protocol for an Environmental Scan of Patient Decision Aids for Seriously Ill People at Risk of Death Facing Choices about Life-Sustaining Treatments.

      Serious Choices: A Protocol for an Environmental Scan of Patient Decision Aids for Seriously Ill People at Risk of Death Facing Choices about Life-Sustaining Treatments.

      Patient. 2017 Aug 20;:

      Authors: Saunders CH, Elwyn G, Kirkland K, Durand MA

      Abstract BACKGROUND: Seriously ill people at high risk of death face difficult decisions, especially concerning the extent of medical intervention.

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    14. Classification of Use Status for Dietary Supplements in Clinical Notes.

      Classification of Use Status for Dietary Supplements in Clinical Notes.

      Classification of Use Status for Dietary Supplements in Clinical Notes.

      Proceedings (IEEE Int Conf Bioinformatics Biomed). 2016 Dec;2016:1054-1061

      Authors: Fan Y, He L, Zhang R

      Abstract Clinical notes contain rich information about dietary supplements, which are critical for detecting signals of dietary supplement side effects and interactions between drugs and supplements. One of the important factors of supplement documentation is usage status, such as started and discontinuation.

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      Mentions: John
    15. Using Pathfinder Networks to Discover Alignment between Expert and Consumer Conceptual Knowledge from Online Vaccine Content.

      Using Pathfinder Networks to Discover Alignment between Expert and Consumer Conceptual Knowledge from Online Vaccine Content.

      Using Pathfinder Networks to Discover Alignment between Expert and Consumer Conceptual Knowledge from Online Vaccine Content.

      J Biomed Inform. 2017 Aug 17;:

      Authors: Amith M, Cunningham R, Savas LS, Boom J, Schvaneveldt R, Tao C, Cohen T

      Abstract This study demonstrates the use of distributed vector representations and Pathfinder Network Scaling (PFNETS) to represent online vaccine content created by health experts and by laypeople.

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    16. Do you vape? Leveraging electronic health records to assess clinician documentation of electronic nicotine delivery system use among adolescents and adults.

      Do you vape? Leveraging electronic health records to assess clinician documentation of electronic nicotine delivery system use among adolescents and adults.

      Do you vape? Leveraging electronic health records to assess clinician documentation of electronic nicotine delivery system use among adolescents and adults.

      Prev Med. 2017 Aug 16;:

      Authors: Young-Wolff KC, Klebaner D, Folck B, Carter-Harris L, Salloum RG, Prochaska JJ, Fogelberg R, Tan ASL

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      Mentions: EHR ASL
    17. Automatic data source identification for clinical trial eligibility criteria resolution.

      Automatic data source identification for clinical trial eligibility criteria resolution.

      AMIA Annu Symp Proc. 2016;2016:1149-1158

      Authors: Shivade C, Hebert C, Regan K, Fosler-Lussier E, Lai AM

      Abstract Clinical trial coordinators refer to both structured and unstructured sources of data when evaluating a subject for eligibility. While some eligibility criteria can be resolved using structured data, some require manual review of clinical notes.

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    18. Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

      Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

      Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

      Methods Inf Med. 2017 Aug 16;56(5):

      Authors: Zhang X, Kim J, Patzer RE, Pitts SR, Patzer A, Schrager JD

      Abstract OBJECTIVE: To describe and compare logistic regression and neural network modeling strategies to predict hospital admission or transfer following initial presentation to Emergency Department (ED) triage with and without the addition of natural language processing elements. METHODS: Using data from the National Hospital Ambulatory Medical Care Survey (NHAMCS), a cross-sectional probability sample of United States EDs from 2012 and 2013 survey years, we developed ...

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    19. The use of natural language processing on pediatric diagnostic radiology reports in the electronic health record to identify deep venous thrombosis in children.

      The use of natural language processing on pediatric diagnostic radiology reports in the electronic health record to identify deep venous thrombosis in children.

      The use of natural language processing on pediatric diagnostic radiology reports in the electronic health record to identify deep venous thrombosis in children.

      J Thromb Thrombolysis. 2017 Aug 16;:

      Authors: Gálvez JA, Pappas JM, Ahumada L, Martin JN, Simpao AF, Rehman MA, Witmer C

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      Mentions: San Mateo NLP
    20. A Clinical Decision Support System for Monitoring Post-Colonoscopy Patient Follow-Up and Scheduling.

      A Clinical Decision Support System for Monitoring Post-Colonoscopy Patient Follow-Up and Scheduling.

      A Clinical Decision Support System for Monitoring Post-Colonoscopy Patient Follow-Up and Scheduling.

      AMIA Jt Summits Transl Sci Proc. 2017;2017:295-301

      Authors: Wadia R, Shifman M, Levin FL, Marenco L, Brandt CA, Cheung KH, Taddei T, Krauthammer M

      Abstract This paper describes a natural language processing (NLP)-based clinical decision support (CDS) system that is geared towards colon cancer care coordinators as the end users.

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      Mentions: NLP
    21. Correlating Lab Test Results in Clinical Notes with Structured Lab Data: A Case Study in HbA1c and Glucose.

      Correlating Lab Test Results in Clinical Notes with Structured Lab Data: A Case Study in HbA1c and Glucose.

      Correlating Lab Test Results in Clinical Notes with Structured Lab Data: A Case Study in HbA1c and Glucose.

      AMIA Jt Summits Transl Sci Proc. 2017;2017:221-228

      Authors: Sijia L, Liwei W, Ihrke D, Chaudhary V, Tao C, Weng C, Liu H

      Abstract It is widely acknowledged that information extraction of unstructured clinical notes using natural language processing (NLP) and text mining is essential for secondary use of clinical data for clinical research and practice.

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      Mentions: Liu
    22. Ground Truth Creation for Complex Clinical NLP Tasks - an Iterative Vetting Approach and Lessons Learned.

      Ground Truth Creation for Complex Clinical NLP Tasks - an Iterative Vetting Approach and Lessons Learned.

      Ground Truth Creation for Complex Clinical NLP Tasks - an Iterative Vetting Approach and Lessons Learned.

      AMIA Jt Summits Transl Sci Proc. 2017;2017:203-212

      Authors: Liang JJ, Tsou CH, Devarakonda MV

      Abstract Natural language processing (NLP) holds the promise of effectively analyzing patient record data to reduce cognitive load on physicians and clinicians in patient care, clinical research, and hospital operations management.

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      Mentions: NLP EHR
    23. Surveillance of Peripheral Arterial Disease Cases Using Natural Language Processing of Clinical Notes.

      Surveillance of Peripheral Arterial Disease Cases Using Natural Language Processing of Clinical Notes.

      Surveillance of Peripheral Arterial Disease Cases Using Natural Language Processing of Clinical Notes.

      AMIA Jt Summits Transl Sci Proc. 2017;2017:28-36

      Authors: Afzal N, Sohn S, Scott CG, Liu H, Kullo IJ, Arruda-Olson AM

      Abstract Peripheral arterial disease (PAD) is a chronic disease that affects millions of people worldwide and yet remains underdiagnosed and undertreated. Early detection is important, because PAD is strongly associated with an increased risk of mortality and morbidity.

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      Mentions: NLP PAD Liu H
    73-96 of 2862 « 1 2 3 4 5 6 7 ... 118 119 120 »
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD