相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study
Ewan Carr et al.
BMC MEDICINE (2021)
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department
Farah E. Shamout et al.
NPJ DIGITAL MEDICINE (2021)
Deep Interpretable Early Warning System for the Detection of Clinical Deterioration
Farah E. Shamout et al.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2020)
A clinical risk score to identify patients with COVID-19 at high risk of critical care admission or death: An observational cohort study
James B. Galloway et al.
JOURNAL OF INFECTION (2020)
An Imbalanced Data Handling Framework for Industrial Big Data Using a Gaussian Process Regression-Based Generative Adversarial Network
Eunseo Oh et al.
SYMMETRY-BASEL (2020)
Cardiovascular Implications of Fatal Outcomes of Patients With Coronavirus Disease 2019 (COVID-19)
Tao Guo et al.
JAMA CARDIOLOGY (2020)
Clinical outcomes of COVID-19 in Wuhan, China: a large cohort study
Jiao Liu et al.
ANNALS OF INTENSIVE CARE (2020)
Improving Clinical Translation of Machine Learning Approaches Through Clinician-Tailored Visual Displays of Black Box Algorithms: Development and Validation
Shannon Wongvibulsin et al.
JMIR MEDICAL INFORMATICS (2020)
Comparison of Early Warning Scoring Systems for Hospitalized Patients With and Without Infection at Risk for In-Hospital Mortality and Transfer to the Intensive Care Unit
Vincent X. Liu et al.
JAMA NETWORK OPEN (2020)
Assessment of the Accuracy of Using ICD-9 Diagnosis Codes to Identify Pneumonia Etiology in Patients Hospitalized With Pneumonia
Thomas L. Higgins et al.
JAMA NETWORK OPEN (2020)
Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU
Guilan Kong et al.
BMC MEDICAL INFORMATICS AND DECISION MAKING (2020)
Correlation analysis between disease severity and inflammation-related parameters in patients with COVID-19: a retrospective study
Jing Gong et al.
BMC INFECTIOUS DISEASES (2020)
Interpretable confidence measures for decision support systems
Jasper van der Waa et al.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES (2020)
Hybrid approach for Anomaly Detection in Time Series Data
Zeineb Ghrib et al.
2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) (2020)
COVID-19 and the elderly: insights into pathogenesis and clinical decision-making
Fabio Perrotta et al.
AGING CLINICAL AND EXPERIMENTAL RESEARCH (2020)
Artificial neural networks improve early outcome prediction and risk classification in out-of-hospital cardiac arrest patients admitted to intensive care
Jesper Johnsson et al.
CRITICAL CARE (2020)
Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records
Hans-Christian Thorsen-Meyer et al.
LANCET DIGITAL HEALTH (2020)
Prospective and External Evaluation of a Machine Learning Model to Predict In-Hospital Mortality of Adults at Time of Admission
Nathan Brajer et al.
JAMA NETWORK OPEN (2020)
An interpretable mortality prediction model for COVID-19 patients
Li Yan et al.
NATURE MACHINE INTELLIGENCE (2020)
An Electronic CKD Phenotype: A Step Forward in Improving Kidney Care
Sri Lekha Tummalapalli et al.
CLINICAL JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY (2019)
Machine learning-based dynamic mortality prediction after traumatic brain injury
Rahul Raj et al.
SCIENTIFIC REPORTS (2019)
Nurse staffing, nursing assistants and hospital mortality: retrospective longitudinal cohort study
Peter Griffiths et al.
BMJ QUALITY & SAFETY (2019)
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
Cynthia Rudin
NATURE MACHINE INTELLIGENCE (2019)
Artificial intelligence in retina
Ursula Schmidt-Erfurth et al.
PROGRESS IN RETINAL AND EYE RESEARCH (2018)
NEWS 2-too little evidence to implement?
Luke E. Hodgson et al.
CLINICAL MEDICINE (2018)
The Number of Comorbidities Predicts Renal Outcomes in Patients with Stage 3-5 Chronic Kidney Disease
Wen-Chin Lee et al.
JOURNAL OF CLINICAL 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)
Interpretable Representation Learning for Healthcare via Capturing Disease Progression through Time
Tian Bai et al.
KDD'18: PROCEEDINGS OF THE 24TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING (2018)
Early hospital mortality prediction of intensive care unit patients using an ensemble learning approach
Aya Awad et al.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2017)
Rates and risk factors associated with hospitalization for pneumonia with ICU admission among adults
Aaron D. Storms et al.
BMC PULMONARY MEDICINE (2017)
Machine learning landscapes and predictions for patient outcomes
Ritankar Das et al.
ROYAL SOCIETY OPEN SCIENCE (2017)
Risk factors for community-acquired pneumonia among adults in Kenya: a case-control study
Esther Muthumbi et al.
PNEUMONIA (2017)
Patient Subtyping via Time-Aware LSTM Networks
Inci M. Baytas et al.
KDD'17: PROCEEDINGS OF THE 23RD ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING (2017)
A mixed-ensemble model for hospital readmission
Lior Turgeman et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2016)
Combining Static and Dynamic Features for Multivariate Sequence Classification
Anna Leontjeva et al.
PROCEEDINGS OF 3RD IEEE/ACM INTERNATIONAL CONFERENCE ON DATA SCIENCE AND ADVANCED ANALYTICS, (DSAA 2016) (2016)
The precision recall curve overcame the optimism of the receiver operating characteristic curve in rare diseases
Brice Ozenne et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2015)
Why the C-statistic is not informative to evaluate early warning scores and what metrics to use
Santiago Romero-Brufau et al.
CRITICAL CARE (2015)
Multicenter Development and Validation of a Risk Stratification Tool for Ward Patients
Matthew M. Churpek et al.
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE (2014)
Gaussian Processes for Personalized e-Health Monitoring With Wearable Sensors
Lei Clifton et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2013)
The effect of comorbidities on risk of intensive care readmission during the same hospitalization: A linked data cohort study
Kwok M. Ho et al.
JOURNAL OF CRITICAL CARE (2009)
An experimental comparison of performance measures for classification
C. Ferri et al.
PATTERN RECOGNITION LETTERS (2009)
Is combining classifiers with stacking better than selecting the best one?
S Dzeroski et al.
MACHINE LEARNING (2004)