Related references
Note: Only part of the references are listed.Leveraging Electronic Health Records and Machine Learning to Tailor Nursing Care for Patients at High Risk for Readmissions
Heather Brom et al.
JOURNAL OF NURSING CARE QUALITY (2020)
Using machine learning to predict 30-day readmissions after posterior lumbar fusion: an NSQIP study involving 23,264 patients
Benjamin S. Hopkins et al.
JOURNAL OF NEUROSURGERY-SPINE (2020)
Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy
Lucas M. Fleuren et al.
INTENSIVE CARE MEDICINE (2020)
Use of electronic medical records in development and validation of risk prediction models of hospital readmission: systematic review
Elham Mahmoudi et al.
BMJ-BRITISH MEDICAL JOURNAL (2020)
Machine Learning Accurately Predicts Short-Term Outcomes Following Open Reduction and Internal Fixation of Ankle Fractures
Robert K. Merrill et al.
JOURNAL OF FOOT & ANKLE SURGERY (2019)
Machine learning modeling for predicting hospital readmission following lumbar laminectomy
Saisanjana Kalagara et al.
JOURNAL OF NEUROSURGERY-SPINE (2019)
Risk of 30-Day Hospital Readmission Among Patients Discharged to Skilled Nursing Facilities: Development and Validation of a Risk-Prediction Model
Anupam Chandra et al.
JOURNAL OF THE AMERICAN MEDICAL DIRECTORS ASSOCIATION (2019)
Deep neural networks in psychiatry
Daniel Durstewitz et al.
MOLECULAR PSYCHIATRY (2019)
Predictive Modeling of the Hospital Readmission Risk from Patients' Claims Data Using Machine Learning: A Case Study on COPD
Xu Min et al.
SCIENTIFIC REPORTS (2019)
Machine Learning to Predict Outcomes in Patients with Acute Gastrointestinal Bleeding: A Systematic Review
Dennis Shung et al.
DIGESTIVE DISEASES AND SCIENCES (2019)
Big data and machine learning algorithms for health-care delivery
Kee Yuan Ngiam et al.
LANCET ONCOLOGY (2019)
Machine Learning in Medicine
Alvin Rajkomar et al.
NEW ENGLAND JOURNAL OF MEDICINE (2019)
High-Risk Phenotypes of Early Psychiatric Readmission in Bipolar Disorder With Comorbid Medical Illness
Juliet Edgcomb et al.
PSYCHOSOMATICS (2019)
Development and Prospective Validation of a Machine Learning-Based Risk of Readmission Model in a Large Military Hospital
Carly Eckert et al.
APPLIED CLINICAL INFORMATICS (2019)
Leveraging Machine Learning Techniques to Forecast Patient Prognosis After Percutaneous Coronary Intervention
Chad J. Zack et al.
JACC-CARDIOVASCULAR INTERVENTIONS (2019)
A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models
Evangelia Christodoulou et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2019)
Can machine learning algorithms accurately predict discharge to nonhome facility and early unplanned readmissions following spinal fusion? Analysis of a national surgical registry
Anshit Goyal et al.
JOURNAL OF NEUROSURGERY-SPINE (2019)
Analysis and prediction of unplanned intensive care unit readmission using recurrent neural networks with long shortterm memory
Yu-Wei Lin et al.
PLOS ONE (2019)
Machine Learning for Health Services Researchers
Patrick Doupe et al.
VALUE IN HEALTH (2019)
Neural networks versus Logistic regression for 30 days all-cause readmission prediction
Ahmed Allam et al.
SCIENTIFIC REPORTS (2019)
Predicting Hospital Readmissions from Home Healthcare in Medicare Beneficiaries
Christine D. Jones et al.
JOURNAL OF THE AMERICAN GERIATRICS SOCIETY (2019)
Machine learning in predicting graft failure following kidney transplantation: A systematic review of published predictive models
Sameera Senanayake et al.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2019)
Potential Impact of Initial Clinical Data on Adjustment of Pediatric Readmission Rates
Mari M. Nakamura et al.
ACADEMIC PEDIATRICS (2019)
Assessing Predictors of Early and Late Hospital Readmission After Kidney Transplantation
Julien Hogan et al.
TRANSPLANTATION DIRECT (2019)
A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data
Sara Bersche Golas et al.
BMC MEDICAL INFORMATICS AND DECISION MAKING (2018)
Predictive models for hospital readmission risk: A systematic review of methods
Arkaitz Artetxe et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2018)
Future Direction for Using Artificial Intelligence to Predict and Manage Hypertension
Chayakrit Krittanawong et al.
CURRENT HYPERTENSION REPORTS (2018)
Predicting Hospital Readmission via Cost-Sensitive Deep Learning
Haishuai Wang et al.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2018)
Big Data and Machine Learning in Health Care
Andrew L. Beam et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2018)
Readmission prediction via deep contextual embedding of clinical concepts
Cao Xiao et al.
PLOS ONE (2018)
Machine Learning and Neurosurgical Outcome Prediction: A Systematic Review
Joeky T. Senders et al.
WORLD NEUROSURGERY (2018)
Comparison of Machine Learning Algorithms for the Prediction of Preventable Hospital Readmissions
Andres Garcia-Arce et al.
JOURNAL FOR HEALTHCARE QUALITY (2018)
Machine learning in major depression: From classification to treatment outcome prediction
Shuang Gao et al.
CNS NEUROSCIENCE & THERAPEUTICS (2018)
Predicting hospital readmission for lupus patients: An RNN-LSTM-based deep-learning methodology
Bhargava K. Reddy et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2018)
Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review
Yena Lee et al.
JOURNAL OF AFFECTIVE DISORDERS (2018)
Predicting the risk of acute care readmissions among rehabilitation inpatients: A machine learning approach
Yajiong Xue et al.
JOURNAL OF BIOMEDICAL INFORMATICS (2018)
eDoctor: machine learning and the future of medicine
G. S. Handelman et al.
JOURNAL OF INTERNAL MEDICINE (2018)
Predicting Intensive Care Unit Readmission with Machine Learning Using Electronic Health Record Data
Juan C. Rojas et al.
ANNALS OF THE AMERICAN THORACIC SOCIETY (2018)
Deep learning for healthcare: review, opportunities and challenges
Riccardo Miotto et al.
BRIEFINGS IN BIOINFORMATICS (2018)
Scalable and accurate deep learning with electronic health records
Alvin Rajkomar et al.
NPJ DIGITAL MEDICINE (2018)
Impact of a Pharmacist-Led Intervention on 30-Day Readmission and Assessment of Factors Predictive of Readmission in African American Men With Heart Failure
DeAngelo McKinley et al.
AMERICAN JOURNAL OF MENS HEALTH (2018)
An introduction and overview of machine learning in neurosurgical care
Joeky T. Senders et al.
ACTA NEUROCHIRURGICA (2018)
Moving beyond regression techniques in cardiovascular risk prediction: applying machine learning to address analytic challenges
Benjamin A. Goldstein et al.
EUROPEAN HEART JOURNAL (2017)
The impact of machine learning techniques in the study of bipolar disorder: A systematic review
Diego Librenza-Garcia et al.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS (2017)
Machine Learning and Prediction in Medicine - Beyond the Peak of Inflated Expectations
Jonathan H. Chen et al.
NEW ENGLAND JOURNAL OF MEDICINE (2017)
Predictors of discharge destination from acute care in patients with traumatic brain injury
Sareh Zarshenas et al.
BMJ OPEN (2017)
A guide to systematic review and meta-analysis of prediction model performance
Thomas P. A. Debray et al.
BMJ-BRITISH MEDICAL JOURNAL (2017)
A guide to systematic review and meta-analysis of prediction model performance
Thomas P. A. Debray et al.
BMJ-BRITISH MEDICAL JOURNAL (2017)
Contribution of temporal data to predictive performance in 30-day readmission of morbidly obese patients
Petra Povalej Brzan et al.
PEERJ (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)
Machine learning and microsimulation techniques on the prognosis of dementia: A systematic literature review
Ana Luiza Dallora et al.
PLOS ONE (2017)
Predicting all-cause risk of 30-day hospital readmission using artificial neural networks
Mehdi Jamei et al.
PLOS ONE (2017)
Predicting Hospital Re-admissions from Nursing Care Data of Hospitalized Patients
Muhammad K. Lodhi et al.
ADVANCES IN DATA MINING: APPLICATIONS AND THEORETICAL ASPECTS, ICDM 2017 (2017)
Texture and art with deep neural networks
Leon A. Gatys et al.
CURRENT OPINION IN NEUROBIOLOGY (2017)
Predictors of 30-Day Readmission Following Inpatient Rehabilitation for Patients at High Risk for Hospital Readmission
Steve R. Fisher et al.
PHYSICAL THERAPY (2016)
A framework for parameter estimation and model selection in kernel deep stacking networks
Thomas Welchowski et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2016)
A mixed-ensemble model for hospital readmission
Lior Turgeman et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2016)
Comparison of predictive modeling approaches for 30-day all-cause non-elective readmission risk
Liping Tong et al.
BMC MEDICAL RESEARCH METHODOLOGY (2016)
Analysis of Machine Learning Techniques for Heart Failure Readmissions
Bobak J. Mortazavi et al.
CIRCULATION-CARDIOVASCULAR QUALITY AND OUTCOMES (2016)
Development of a Nonparametric Predictive Model for Readmission Risk in Elderly Adults After Colon and Rectal Cancer Surgery
Heather Yeo et al.
JOURNAL OF THE AMERICAN GERIATRICS SOCIETY (2016)
Analysis of Machine Learning Techniques for Heart Failure Readmissions
Bobak J. Mortazavi et al.
CIRCULATION-CARDIOVASCULAR QUALITY AND OUTCOMES (2016)
Utility of models to predict 28-day or 30-day unplanned hospital readmissions: an updated systematic review
Huaqiong Zhou et al.
BMJ OPEN (2016)
Predicting early psychiatric readmission with natural language processing of narrative discharge summaries
A. Rumshisky et al.
TRANSLATIONAL PSYCHIATRY (2016)
Assessing risk of hospital readmissions for improving medical practice
Parimal Kulkarni et al.
HEALTH CARE MANAGEMENT SCIENCE (2016)
Machine learning applications in cancer prognosis and prediction
Konstantina Kourou et al.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL (2015)
Identification of individuals with ADHD using the dean-woodcock sensory motor battery and a boosted tree algorithm
Holmes W. Finch et al.
BEHAVIOR RESEARCH METHODS (2015)
Effect of a Postdischarge Virtual Ward on Readmission or Death for High-Risk Patients A Randomized Clinical Trial
Irfan A. Dhalla et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2014)
Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies: The CHARMS Checklist
Karel G. M. Moons et al.
PLOS MEDICINE (2014)
Assessing Bias in Studies of Prognostic Factors
Jill A. Hayden et al.
ANNALS OF INTERNAL MEDICINE (2013)
Diagnoses and Timing of 30-Day Readmissions After Hospitalization for Heart Failure, Acute Myocardial Infarction, or Pneumonia
Kumar Dharmarajan et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2013)
An Administrative Claims Measure Suitable for Profiling Hospital Performance Based on 30-Day All-Cause Readmission Rates Among Patients With Acute Myocardial Infarction
Harlan M. Krumholz et al.
CIRCULATION-CARDIOVASCULAR QUALITY AND OUTCOMES (2011)
Hospital Readmissions and the Affordable Care Act Paying for Coordinated Quality Care
Robert P. Kocher et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2011)
Risk Prediction Models for Hospital Readmission A Systematic Review
Devan Kansagara et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2011)
Development, Validation, and Results of a Measure of 30-Day Readmission Following Hospitalization for Pneumonia
Peter K. Lindenauer et al.
JOURNAL OF HOSPITAL MEDICINE (2011)
National Patterns of Risk-Standardized Mortality and Readmission for Acute Myocardial Infarction and Heart Failure Update on Publicly Reported Outcomes Measures Based on the 2010 Release
Susannah M. Bernheim et al.
CIRCULATION-CARDIOVASCULAR QUALITY AND OUTCOMES (2010)
Rehospitalizations among Patients in the Medicare Fee-for-Service Program
Stephen F. Jencks et al.
NEW ENGLAND JOURNAL OF MEDICINE (2009)
An Administrative Claims Measure Suitable for Profiling Hospital Performance on the Basis of 30-Day All-Cause Readmission Rates Among Patients With Heart Failure
Patricia S. Keenan et al.
CIRCULATION-CARDIOVASCULAR QUALITY AND OUTCOMES (2008)
A working guide to boosted regression trees
J. Elith et al.
JOURNAL OF ANIMAL ECOLOGY (2008)
Share Paper
