Clinical decision support with automated text processing for cervical cancer screening. - Wikidata - wikimedia - TriplyDB

Clinical decision support with automated text processing for cervical cancer screening.

Clinical decision support with automated text processing for cervical cancer screening.

http://www.wikidata.org/entity/Q36175210

about

Use of health information technology to reduce diagnostic errors."Big data" and the electronic health record.Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis.Natural Language Processing-Enabled and Conventional Data Capture Methods for Input to Electronic Health Records: A Comparative Usability Study Agreement of Medicaid claims and electronic health records for assessing preventive care quality among adults.Automated recommendation for cervical cancer screening and surveillance.Using Natural Language Processing to Extract Abnormal Results From Cancer Screening Reports.Open Source Clinical NLP - More than Any Single System.Text Classification towards Detecting Misdiagnosis of an Epilepsy Syndrome in a Pediatric Population.Annotating longitudinal clinical narratives for de-identification: The 2014 i2b2/UTHealth corpus.Granular Quality Reporting for Cervical Cytology Testing.Natural language processing in pathology: a scoping review.Recognizing Disjoint Clinical Concepts in Clinical Text Using Machine Learning-based Methods Formative evaluation of the accuracy of a clinical decision support system for cervical cancer screening.Using statistical text classification to identify health information technology incidents.Combining rules and machine learning for extraction of temporal expressions and events from clinical narratives.An information extraction framework for cohort identification using electronic health records.Development of a decision support system for the practice of responsible self-medication.Using automatically extracted information from mammography reports for decision-support.Developing and evaluating an automated appendicitis risk stratification algorithm for pediatric patients in the emergency department.Learning regular expressions for clinical text classification.Impact of Patient Reminders on Papanicolaou Test Completion for High-Risk Patients Identified by a Clinical Decision Support System.Improving the Accuracy of a Clinical Decision Support System for Cervical Cancer Screening and Surveillance.

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P2860

Clinical decision support with automated text processing for cervical cancer screening.

http://www.wikidata.org/entity/Q36175210

description

2012 nî lūn-bûn

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2012年の論文

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2012年論文

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2012年論文

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2012年論文

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2012年论文

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name

Clinical decision support with automated text processing for cervical cancer screening.

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Clinical decision support with automated text processing for cervical cancer screening.

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type

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Clinical decision support with automated text processing for cervical cancer screening.

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Clinical decision support with automated text processing for cervical cancer screening.

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Clinical decision support with automated text processing for cervical cancer screening.

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Clinical decision support with automated text processing for cervical cancer screening.

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AMIAJNL-2012-000820

P1433

Journal of the American Medical Informatics Association

P1476

Clinical decision support with automated text processing for cervical cancer screening.

@en

P2093

Hongfang Liu

http://www.w3.org/2001/XMLSchema#string

Kathy L MacLaughlin

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Kavishwar B Wagholikar

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Michael R Henry

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Rajeev Chaudhry

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Robert A Greenes

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Ronald A Hankey

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P2860

Global cancer statistics

Natural language processing: an introduction

Modeling Paradigms for Medical Diagnostic Decision Support: A Survey and Future Directions

Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program

Extracting information from textual documents in the electronic health record: a review of recent research.

Electronic Support for Public Health: validated case finding and reporting for notifiable diseases using electronic medical data.

Characterization of patients who suffer asthma exacerbations using data extracted from electronic medical records.

What can natural language processing do for clinical decision support?

Adherence to cervical cancer screening guidelines for U.S. women aged 25-64: data from the 2005 Health Information National Trends Survey (HINTS).

Tracking abnormal cervical cancer screening: evaluation of an EMR-based intervention.

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833-839

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10.1136/AMIAJNL-2012-000820

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5

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19

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224866593

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22542812

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3422840

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