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Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease

PloS one, 2018-08, Vol.13 (8), p.e0202344-e0202344

2018

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Blood pressure and incidence of twelve cardiovascular diseases: lifetime risks, healthy life-years lost, and age-specific associations in 1·25 million people

The Lancet (British edition), 2014-05, Vol.383 (9932), p.1899-1911

2014

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Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using MICE: A CALIBER Study

American journal of epidemiology, 2014-03, Vol.179 (6), p.764-774

2014

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Association between clinically recorded alcohol consumption and initial presentation of 12 cardiovascular diseases: population based cohort study using linked health records

BMJ (Online), 2017-03, Vol.356, p.j909

2017

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Digital technology and patient and public involvement (PPI) in routine care and clinical research-A pilot study

PloS one, 2023-02, Vol.18 (2), p.e0278260-e0278260

2023

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Extracting diagnoses and investigation results from unstructured text in electronic health records by semi-supervised machine learning

PloS one, 2012-01, Vol.7 (1), p.e30412-e30412

2012

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Defining disease phenotypes using national linked electronic health records: a case study of atrial fibrillation

PloS one, 2014-11, Vol.9 (11), p.e110900-e110900

2014

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Reproducible disease phenotyping at scale: Example of coronary artery disease in UK Biobank

PloS one, 2022-04, Vol.17 (4), p.e0264828-e0264828

2022

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Data gaps in electronic health record (EHR) systems: An audit of problem list completeness during the COVID-19 pandemic

International journal of medical informatics (Shannon, Ireland), 2021-06, Vol.150, p.104452-104452, Article 104452

2021

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Bleeding in cardiac patients prescribed antithrombotic drugs: electronic health record phenotyping algorithms, incidence, trends and prognosis

BMC medicine, 2019-11, Vol.17 (1), p.206-14, Article 206

2019

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An informatics consult approach for generating clinical evidence for treatment decisions

BMC medical informatics and decision making, 2021-10, Vol.21 (1), p.281-281, Article 281

2021

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The freetext matching algorithm: a computer program to extract diagnoses and causes of death from unstructured text in electronic health records

BMC medical informatics and decision making, 2012-08, Vol.12 (1), p.88-88, Article 88

2012

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Natural language processing for disease phenotyping in UK primary care records for research: a pilot study in myocardial infarction and death

Journal of biomedical semantics, 2019-11, Vol.10 (Suppl 1), p.20-20, Article 20

2019

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Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances

Journal of biomedical informatics, 2018-12, Vol.88, p.11-19

2018

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Understanding Views Around the Creation of a Consented, Donated Databank of Clinical Free Text to Develop and Train Natural Language Processing Models for Research: Focus Group Interviews With Stakeholders

JMIR medical informatics, 2023-05, Vol.11, p.e45534-e45534

2023

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Prognostic significance of troponin level in 3121 patients presenting with atrial fibrillation (The NIHR Health Informatics Collaborative TROP-AF study)

Journal of the American Heart Association, 2020-04, Vol.9 (7), p.e013684-e013684

2020

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Prognostic Significance of Ventricular Arrhythmias in 13 444 Patients With Acute Coronary Syndrome: A Retrospective Cohort Study Based on Routine Clinical Data (NIHR Health Informatics Collaborative VA-ACS Study)

Journal of the American Heart Association, 2022-03, Vol.11 (6), p.e024260-e024260

2022

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Threshold haemoglobin levels and the prognosis of stable coronary disease: two new cohorts and a systematic review and meta-analysis

PLoS medicine, 2011-05, Vol.8 (5), p.e1000439-e1000439

2011

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UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER

Journal of the American Medical Informatics Association : JAMIA, 2019-12, Vol.26 (12), p.1545-1559

2019

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Artificial intelligence and machine learning for clinical pharmacology

British journal of clinical pharmacology, 2024-03, Vol.90 (3), p.629-639

2024

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Data Resource Profile: Cardiovascular disease research using linked bespoke studies and electronic health records (CALIBER)

International journal of epidemiology, 2012-12, Vol.41 (6), p.1625-1638

2012

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Prognostic burden of heart failure recorded in primary care, acute hospital admissions, or both: a population‐based linked electronic health record cohort study in 2.1 million people

European journal of heart failure, 2017-09, Vol.19 (9), p.1119-1127

2017

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Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease

Blood pressure and incidence of twelve cardiovascular diseases: lifetime risks, healthy life-years lost, and age-specific associations in 1·25 million people

Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using MICE: A CALIBER Study

Symptoms and risk factors for long COVID in non-hospitalized adults

Association between clinically recorded alcohol consumption and initial presentation of 12 cardiovascular diseases: population based cohort study using linked health records

Mortality risk prediction of high-sensitivity C-reactive protein in suspected acute coronary syndrome: A cohort study

Digital technology and patient and public involvement (PPI) in routine care and clinical research-A pilot study

Extracting diagnoses and investigation results from unstructured text in electronic health records by semi-supervised machine learning

Defining disease phenotypes using national linked electronic health records: a case study of atrial fibrillation

Reproducible disease phenotyping at scale: Example of coronary artery disease in UK Biobank

Data gaps in electronic health record (EHR) systems: An audit of problem list completeness during the COVID-19 pandemic

Bleeding in cardiac patients prescribed antithrombotic drugs: electronic health record phenotyping algorithms, incidence, trends and prognosis

An informatics consult approach for generating clinical evidence for treatment decisions

The freetext matching algorithm: a computer program to extract diagnoses and causes of death from unstructured text in electronic health records

Natural language processing for disease phenotyping in UK primary care records for research: a pilot study in myocardial infarction and death

Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances

Understanding Views Around the Creation of a Consented, Donated Databank of Clinical Free Text to Develop and Train Natural Language Processing Models for Research: Focus Group Interviews With Stakeholders

Prognostic significance of troponin level in 3121 patients presenting with atrial fibrillation (The NIHR Health Informatics Collaborative TROP-AF study)

Prognostic Significance of Ventricular Arrhythmias in 13 444 Patients With Acute Coronary Syndrome: A Retrospective Cohort Study Based on Routine Clinical Data (NIHR Health Informatics Collaborative VA-ACS Study)

Threshold haemoglobin levels and the prognosis of stable coronary disease: two new cohorts and a systematic review and meta-analysis

UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER

Artificial intelligence and machine learning for clinical pharmacology

Invasive versus non-invasive management of older patients with non-ST elevation myocardial infarction (SENIOR-NSTEMI): a cohort study based on routine clinical data

Data Resource Profile: Cardiovascular disease research using linked bespoke studies and electronic health records (CALIBER)

Prognostic burden of heart failure recorded in primary care, acute hospital admissions, or both: a population‐based linked electronic health record cohort study in 2.1 million people

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