Related references
Note: Only part of the references are listed.Development, evaluation, and validation of machine learning models for COVID-19 detection based on routine blood tests
Federico Cabitza et al.
CLINICAL CHEMISTRY AND LABORATORY MEDICINE (2021)
The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation
Davide Chicco et al.
BIODATA MINING (2021)
Estimation of required sample size for external validation of risk models for binary outcomes
Menelaos Pavlou et al.
STATISTICAL METHODS IN MEDICAL RESEARCH (2021)
The need to separate the wheat from the chaff in medical informatics Introducing a comprehensive checklist for the (self)-assessment of medical AI studies
Federico Cabitza et al.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2021)
External validation of clinical prediction models: simulation-based sample size calculations were more reliable than rules-of-thumb
Kym I. E. Snell et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2021)
Minimum sample size for external validation of a clinical prediction model with a binary outcome
Richard D. Riley et al.
STATISTICS IN MEDICINE (2021)
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
Michael Roberts et al.
NATURE MACHINE INTELLIGENCE (2021)
Minimum sample size for external validation of a clinical prediction model with a continuous outcome
Lucinda Archer et al.
STATISTICS IN MEDICINE (2021)
Systematic review and meta-analysis of within-subject and between-subject biological variation estimates of 20 haematological parameters
Abdurrahman Coskun et al.
CLINICAL CHEMISTRY AND LABORATORY MEDICINE (2020)
Challenges to the Reproducibility of Machine Learning Models in Health Care
Andrew L. Beam et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2020)
Routine blood tests as a potential diagnostic tool for COVID-19
Davide Ferrari et al.
CLINICAL CHEMISTRY AND LABORATORY MEDICINE (2020)
Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks
Ali Abbasian Ardakani et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2020)
Automated detection of COVID-19 cases using deep neural networks with X-ray images
Tulin Ozturk et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2020)
MINIMAR (MINimum Information for Medical Al Reporting): Developing reporting standards for artificial intelligence in health care
Tina Hernandez-Boussard et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2020)
As if sand were stone. New concepts and metrics to probe the ground on which to build trustable AI
Federico Cabitza et al.
BMC MEDICAL INFORMATICS AND DECISION MAKING (2020)
Routine Laboratory Blood Tests Predict SARS-CoV-2 Infection Using Machine Learning
He S. Yang et al.
CLINICAL CHEMISTRY (2020)
COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios
Rodolfo M. Pereira et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2020)
The data representativeness criterion: Predicting the performance of supervised classification based on data set similarity
Evelien Schat et al.
PLOS ONE (2020)
Development and External Validation of a Machine Learning Tool to Rule Out COVID-19 Among Adults in the Emergency Department Using Routine Blood Tests: A Large, Multicenter, Real-World Study
Timothy B. Plante et al.
JOURNAL OF MEDICAL INTERNET RESEARCH (2020)
The optimal diagnostic methods for COVID-19
Tinotenda A. Harahwa et al.
DIAGNOSIS (2020)
Cross-site transportability of an explainable artificial intelligence model for acute kidney injury prediction
Xing Song et al.
NATURE COMMUNICATIONS (2020)
CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images
Asif Iqbal Khan et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2020)
Explainable Deep Learning for Pulmonary Disease and Coronavirus COVID-19 Detection from X-rays
Luca Brunese et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2020)
The proof of the pudding: in praise of a culture of real-world validation for medical artificial intelligence
Federico Cabitza et al.
ANNALS OF TRANSLATIONAL MEDICINE (2019)
Machine learning algorithm validation with a limited sample size
Andrius Vabalas et al.
PLOS ONE (2019)
Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images: a retrospective, multicohort, diagnostic study
Xiangchun Li et al.
LANCET ONCOLOGY (2019)
Using the Data Agreement Criterion to Rank Experts' Beliefs
Duco Veen et al.
ENTROPY (2018)
Analysis of the factors influencing healthcare professionals' adoption of mobile electronic medical record (EMR) using the unified theory of acceptance and use of technology (UTAUT) in a tertiary hospital
Seok Kim et al.
BMC MEDICAL INFORMATICS AND DECISION MAKING (2016)
Sample size considerations for the external validation of a multivariable prognostic model: a resampling study
Gary S. Collins et al.
STATISTICS IN MEDICINE (2016)
Prediction models need appropriate internal, internal-external, and external validation
Ewout W. Steyerberg et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2016)
A calibration hierarchy for risk models was defined: from utopia to empirical data
Ben Van Calster et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2016)
POINTS OF SIGNIFICANCE Model selection and overfitting
Jake Lever et al.
NATURE METHODS (2016)
External validation of multivariable prediction models: a systematic review of methodological conduct and reporting
Gary S. Collins et al.
BMC MEDICAL RESEARCH METHODOLOGY (2014)
On the effectiveness of preprocessing methods when dealing with different levels of class imbalance
V. Garcia et al.
KNOWLEDGE-BASED SYSTEMS (2012)
Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies
Valentin Rousson et al.
BMC MEDICAL INFORMATICS AND DECISION MAKING (2011)
Explaining physicians' acceptance of EHCR systems: An extension of TAM with trust and risk factors
Jose Manuel Ortega Egea et al.
COMPUTERS IN HUMAN BEHAVIOR (2011)
Race-specific WBC and neutrophil count reference intervals
E. -M. Lim et al.
INTERNATIONAL JOURNAL OF LABORATORY HEMATOLOGY (2010)
Receiver Operating Characteristic Curve in Diagnostic Test Assessment
Jayawant N. Mandrekar
JOURNAL OF THORACIC ONCOLOGY (2010)
Estimating classification error rate: Repeated cross-validation, repeated hold-out and bootstrap
Ji-Hyun Kim
COMPUTATIONAL STATISTICS & DATA ANALYSIS (2009)
Diagnostics of prior-data agreement in applied Bayesian analysis
Nicolas Bousquet
JOURNAL OF APPLIED STATISTICS (2008)
Sampling Uncertainty and Confidence Intervals for the Brier Score and Brier Skill Score
A. Allen Bradley et al.
WEATHER AND FORECASTING (2008)
Practical experiences on the necessity of external validation
I. R. Koenig et al.
STATISTICS IN MEDICINE (2007)
Substantial effective sample sizes were required for external validation studies of predictive logistic regression models
Y Vergouwe et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2005)
External validation is necessary in, prediction research: A clinical example
SE Bleeker et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2003)
Internal and external validation of predictive models: A simulation study of bias and precision in small samples
EW Steyerberg et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2003)
Internal validation of predictive models: Efficiency of some procedures for logistic regression analysis
EW Steyerberg et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2001)
Share Paper
