AIMC Topic: ROC Curve

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Predicting Long-Term Outcomes After Poor-Grade Aneurysmal Subarachnoid Hemorrhage Using Decision Tree Modeling.

Neurosurgery
BACKGROUND: Despite advances in the treatment of poor-grade aneurysmal subarachnoid hemorrhage (aSAH), predicting the long-term outcome of aSAH remains challenging, although essential.

Machine Learning Assessment of Left Ventricular Diastolic Function Based on Electrocardiographic Features.

Journal of the American College of Cardiology
BACKGROUND: Left ventricular (LV) diastolic dysfunction is recognized as playing a major role in the pathophysiology of heart failure; however, clinical tools for identifying diastolic dysfunction before echocardiography remain imprecise.

Classification of cell morphology with quantitative phase microscopy and machine learning.

Optics express
We describe and compare two machine learning approaches for cell classification based on label-free quantitative phase imaging with transport of intensity equation methods. In one approach, we design a multilevel integrated machine learning classifie...

An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study.

The Lancet. Digital health
BACKGROUND: There is high demand to develop computer-assisted diagnostic tools to evaluate prostate core needle biopsies (CNBs), but little clinical validation and a lack of clinical deployment of such tools. We report here on a blinded clinical vali...

Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia.

IEEE transactions on medical imaging
The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,436,000 people in more than 200 countries and territories as of April 9, 2020. Detecting COVID-19 at early stage is essential to deliver proper h...

sureLDA: A multidisease automated phenotyping method for the electronic health record.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: A major bottleneck hindering utilization of electronic health record data for translational research is the lack of precise phenotype labels. Chart review as well as rule-based and supervised phenotyping approaches require laborious expert...

Constructing co-occurrence network embeddings to assist association extraction for COVID-19 and other coronavirus infectious diseases.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: As coronavirus disease 2019 (COVID-19) started its rapid emergence and gradually transformed into an unprecedented pandemic, the need for having a knowledge repository for the disease became crucial. To address this issue, a new COVID-19 m...

An artificial intelligence approach to COVID-19 infection risk assessment in virtual visits: A case report.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: In an effort to improve the efficiency of computer algorithms applied to screening for coronavirus disease 2019 (COVID-19) testing, we used natural language processing and artificial intelligence-based methods with unstructured patient dat...

Prediction of all-cause mortality in haemodialysis patients using a Bayesian network.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
BACKGROUND: All-cause mortality in haemodialysis (HD) is high, reaching 15.6% in the first year according to the European Renal Association.

Validating clinical threshold values for a dashboard view of the compensatory reserve measurement for hemorrhage detection.

The journal of trauma and acute care surgery
BACKGROUND: Compensatory reserve measurement (CRM) is a novel noninvasive monitoring technology designed to assess physiologic reserve using feature interrogation of arterial pulse waveforms. This study was conducted to validate clinically relevant C...