AIMC Topic: Predictive Value of Tests

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Diagnostic performance of deep-learning-based screening methods for diabetic retinopathy in primary care-A meta-analysis.

PloS one Aug 10, 2021
BACKGROUND: Diabetic retinopathy (DR) affects 10-24% of patients with diabetes mellitus type 1 or 2 in the primary care (PC) sector. As early detection is crucial for treatment, deep learning screening methods in PC setting could potentially aid in a...
Primary Health Care Mass Screening Predictive Value of Tests Humans Odds Ratio Diabetic Retinopathy Publication Bias Deep Learning ROC Curve
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Development and validation of a new diabetes index for the risk classification of present and new-onset diabetes: multicohort study.

Scientific reports Aug 3, 2021
In this study, we aimed to propose a novel diabetes index for the risk classification based on machine learning techniques with a high accuracy for diabetes mellitus. Upon analyzing their demographic and biochemical data, we classified the 2013-16 Ko...
Humans Machine Learning Prospective Studies Incidence ROC Curve Diabetes Mellitus Predictive Value of Tests Age of Onset Republic of Korea Female Aged Male Middle Aged
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Differentiation of Active Corneal Infections from Healed Scars Using Deep Learning.

Ophthalmology Aug 2, 2021
PURPOSE: To develop and evaluate an automated, portable algorithm to differentiate active corneal ulcers from healed scars using only external photographs.
Corneal Ulcer Eye Infections, Fungal False Positive Reactions Eye Infections, Bacterial Photography Humans Slit Lamp Microscopy Algorithms ROC Curve Retrospective Studies Wound Healing Sensitivity and Specificity Predictive Value of Tests Deep Learning Area Under Curve Cicatrix
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Development and Assessment of an Interpretable Machine Learning Triage Tool for Estimating Mortality After Emergency Admissions.

JAMA network open Aug 2, 2021
IMPORTANCE: Triage in the emergency department (ED) is a complex clinical judgment based on the tacit understanding of the patient's likelihood of survival, availability of medical resources, and local practices. Although a scoring tool could be valu...
Reproducibility of Results Risk Factors Aged Male Middle Aged Humans Machine Learning Retrospective Studies Female Singapore Tertiary Care Centers Benchmarking Patient Acuity Patient Admission Risk Assessment Predictive Value of Tests Triage Emergency Service, Hospital
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Using the Super Learner algorithm to predict risk of 30-day readmission after bariatric surgery in the United States.

Surgery Jul 31, 2021
BACKGROUND: Risk prediction models that estimate patient probabilities of adverse events are commonly deployed in bariatric surgery. The objective was to validate a machine learning (Super Learner) prediction model of 30-day readmission after bariatr...
Obesity, Morbid Patient Readmission Risk Factors Adult ROC Curve Humans Male Logistic Models Machine Learning Middle Aged Predictive Value of Tests Algorithms Postoperative Complications Bariatric Surgery Retrospective Studies Female
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Machine-Learning-Derived Model for the Stratification of Cardiovascular risk in Patients with Ischemic Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Jul 31, 2021
UNLABELLED: Background Stratification of cardiovascular risk in patients with ischemic stroke is important as it may inform management strategies. We aimed to develop a machine-learning-derived prognostic model for the prediction of cardiovascular ri...
Time Factors Predictive Value of Tests Ischemic Stroke Humans Registries Machine Learning Heart Disease Risk Factors Decision Support Techniques Prognosis Male Retrospective Studies Clinical Decision-Making Cardiovascular Diseases Female Middle Aged Reproducibility of Results Risk Assessment Aged Aged, 80 and over
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Improving the predictive potential of diffusion MRI in schizophrenia using normative models-Towards subject-level classification.

Human brain mapping Jul 29, 2021
Diffusion MRI studies consistently report group differences in white matter between individuals diagnosed with schizophrenia and healthy controls. Nevertheless, the abnormalities found at the group-level are often not observed at the individual level...
Female Young Adult Humans Adult Machine Learning Precision Medicine Male Models, Theoretical Middle Aged Predictive Value of Tests Schizophrenia White Matter Diffusion Tensor Imaging
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Deep radiomics-based survival prediction in patients with chronic obstructive pulmonary disease.

Scientific reports Jul 26, 2021
Heterogeneous clinical manifestations and progression of chronic obstructive pulmonary disease (COPD) affect patient health risk assessment, stratification, and management. Pulmonary function tests are used to diagnose and classify the severity of CO...
Deep Learning Cohort Studies Malaysia Predictive Value of Tests Survival Analysis Respiratory Function Tests Female Humans Aged Neural Networks, Computer Pulmonary Disease, Chronic Obstructive Tomography, X-Ray Computed Male Republic of Korea Middle Aged
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Predicting subclinical psychotic-like experiences on a continuum using machine learning.

NeuroImage Jul 22, 2021
Previous studies applying machine learning methods to psychosis have primarily been concerned with the binary classification of chronic schizophrenia patients and healthy controls. The aim of this study was to use electroencephalographic (EEG) data a...
Electroencephalography Psychotic Disorders Proof of Concept Study Acoustic Stimulation Asymptomatic Diseases Adult Male Adolescent Predictive Value of Tests Auditory Perception Humans Machine Learning Female Young Adult
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Artificial Intelligence-Enabled ECG to Identify Silent Atrial Fibrillation in Embolic Stroke of Unknown Source.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Jul 22, 2021
OBJECTIVES: Embolic strokes of unknown source (ESUS) are common and often suspected to be caused by unrecognized paroxysmal atrial fibrillation (AF). An AI-enabled ECG (AI-ECG) during sinus rhythm has been shown to identify patients with unrecognized...
Signal Processing, Computer-Assisted Registries Electrocardiography, Ambulatory Atrial Fibrillation Heart Rate Embolic Stroke Middle Aged Risk Assessment Time Factors Action Potentials Predictive Value of Tests Hospitalization Aged Aged, 80 and over Male Humans Artificial Intelligence Female Risk Factors
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