Related references
Note: Only part of the references are listed.Estimation of the epidemiology of dementia and associated neuropsychiatric symptoms by applying machine learning to real-world data
Javier Mar et al.
REVISTA DE PSIQUIATRIA Y SALUD MENTAL (2022)
Automated detection of patients with dementia whose symptoms have been identified in primary care but have no formal diagnosis: a retrospective case-control study using electronic primary care records
Elizabeth Ford et al.
BMJ OPEN (2021)
Modeling Large Sparse Data for Feature Selection: Hospital Admission Predictions of the Dementia Patients Using Primary Care Electronic Health Records
G. A. V. I. N. TSANG et al.
IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE (2021)
Machine Learning in Epidemiology and Health Outcomes Research
Timothy L. Wiemken et al.
ANNUAL REVIEW OF PUBLIC HEALTH, VOL 41 (2020)
Predicting dementia with routine care EMR data
Zina Ben Miled et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2020)
Action-Informed Artificial Intelligence-Matching the Algorithm to the Problem
Christopher J. Lindsell et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2020)
Learning clinical networks from medical records based on information estimates in mixed-type data
Vincent Cabeli et al.
PLOS COMPUTATIONAL BIOLOGY (2020)
Validation of Random Forest Machine Learning Models to Predict Dementia-Related Neuropsychiatric Symptoms in Real-World Data
Javier Mar et al.
JOURNAL OF ALZHEIMERS DISEASE (2020)
Risk prediction of delirium in hospitalized patients using machine learning: An implementation and prospective evaluation study
Stefanie Jauk et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2020)
Deep neural network models for identifying incident dementia using claims and EHR datasets
Vijay S. Nori et al.
PLOS ONE (2020)
Comparison of Machine Learning Methods With Traditional Models for Use of Administrative Claims With Electronic Medical Records to Predict Heart Failure Outcomes
Rishi J. Desai et al.
JAMA NETWORK OPEN (2020)
Free-Text Documentation of Dementia Symptoms in Home Healthcare: A Natural Language Processing Study
Maxim Topaz et al.
GERONTOLOGY AND GERIATRIC MEDICINE (2020)
Implementation and Use of Disease Diagnosis Systems for Electronic Medical Records Based on Machine Learning: A Complete Review
Jahanzaib Latif et al.
IEEE ACCESS (2020)
Precision health through prediction modelling: factors to consider before implementing a prediction model in clinical practice
Mohammad Z. I. Chowdhury et al.
JOURNAL OF PRIMARY HEALTH CARE (2020)
Machine learning prediction of incidence of Alzheimer's disease using large-scale administrative health data
Ji Hwan Park et al.
NPJ DIGITAL MEDICINE (2020)
Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges
David Thesmar et al.
PHARMACOECONOMICS (2019)
Reporting of artificial intelligence prediction models
Gary S. Collins et al.
LANCET (2019)
Detection of probable dementia cases in undiagnosed patients using structured and unstructured electronic health records
Yijun Shao et al.
BMC MEDICAL INFORMATICS AND DECISION MAKING (2019)
What is Machine Learning? A Primer for the Epidemiologist
Qifang Bi et al.
AMERICAN JOURNAL OF EPIDEMIOLOGY (2019)
Soft clustering using real-world data for the identification of multimorbidity patterns in an elderly population: cross-sectional study in a Mediterranean population
Concepcion Violan et al.
BMJ OPEN (2019)
Artificial Intelligence for Mental Health and Mental Illnesses: an Overview
Sarah Graham et al.
CURRENT PSYCHIATRY REPORTS (2019)
Machine learning for comprehensive forecasting of Alzheimer's Disease progression
Charles K. Fisher et al.
SCIENTIFIC REPORTS (2019)
PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration
Karel G. M. Moons et al.
ANNALS OF INTERNAL MEDICINE (2019)
PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies
Robert F. Wolff et al.
ANNALS OF INTERNAL MEDICINE (2019)
Artificial Intelligence Transforms the Future of Health Care
Nariman Noorbakhsh-Sabet et al.
AMERICAN JOURNAL OF MEDICINE (2019)
Identifying vulnerable older adult populations by contextualizing geriatric syndrome information in clinical notes of electronic health records
Tao Chen et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2019)
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
Cynthia Rudin
NATURE MACHINE INTELLIGENCE (2019)
Development and Validation of a Deep Learning Algorithm for Mortality Prediction in Selecting Patients With Dementia for Earlier Palliative Care Interventions
Liqin Wang et al.
JAMA NETWORK OPEN (2019)
The Value of Unstructured Electronic Health Record Data in Geriatric Syndrome Case Identification
Hadi Kharrazi et al.
JOURNAL OF THE AMERICAN GERIATRICS SOCIETY (2018)
Big data hurdles in precision medicine and precision public health
Mattia Prosperi et al.
BMC MEDICAL INFORMATICS AND DECISION MAKING (2018)
Performance of Electronic Prediction Rules for Prevalent Delirium at Hospital Admission
Christopher W. Halladay et al.
JAMA NETWORK OPEN (2018)
A guide to systematic review and meta-analysis of prediction model performance
Thomas P. A. Debray et al.
BMJ-BRITISH MEDICAL JOURNAL (2017)
Longitudinal Study-Based Dementia Prediction for Public Health
HeeChel Kim et al.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2017)
Comparing clinician descriptions of frailty and geriatric syndromes using electronic health records: a retrospective cohort study
Laura J. Anzaldi et al.
BMC GERIATRICS (2017)
A guide to systematic review and meta-analysis of prediction model performance
Thomas P. A. Debray et al.
BMJ-BRITISH MEDICAL JOURNAL (2017)
Prediction of 30-Day All-Cause Readmissions in Patients Hospitalized for Heart Failure Comparison of Machine Learning and Other Statistical Approaches
Jarrod D. Frizzell et al.
JAMA CARDIOLOGY (2017)
Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View
Wei Luo et al.
JOURNAL OF MEDICAL INTERNET RESEARCH (2016)
Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement
Gary S. Collins et al.
BMC MEDICINE (2015)
Using methods from the data-mining and machine-learning literature for disease classification and prediction: a case study examining classification of heart failure subtypes
Peter C. Austin et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2013)
Which method predicts recidivism best?: a comparison of statistical, machine learning and data mining predictive models
N. Tollenaar et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY (2013)
QUADAS-2: A Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies
Penny F. Whiting et al.
ANNALS OF INTERNAL MEDICINE (2011)
The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration
Alessandro Liberati et al.
PLOS MEDICINE (2009)
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement
David Moher et al.
BMJ-BRITISH MEDICAL JOURNAL (2009)