AIMC Topic: ROC Curve

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Accurate and generalizable quantitative scoring of liver steatosis from ultrasound images scalable deep learning.

World journal of gastroenterology Jun 14, 2022
BACKGROUND: Hepatic steatosis is a major cause of chronic liver disease. Two-dimensional (2D) ultrasound is the most widely used non-invasive tool for screening and monitoring, but associated diagnoses are highly subjective.
Fatty Liver Liver Non-alcoholic Fatty Liver Disease Reproducibility of Results Deep Learning ROC Curve Humans Elasticity Imaging Techniques Retrospective Studies
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Parkland Trauma Index of Mortality: Real-Time Predictive Model for Trauma Patients.

Journal of orthopaedic trauma Jun 1, 2022
OBJECTIVE: Vital signs and laboratory values are used to guide decisions to use damage control techniques in lieu of early definitive fracture fixation. Previous models attempted to predict mortality risk but have limited utility. There is a need for...
Retrospective Studies Humans Hospitalization ROC Curve Machine Learning Predictive Value of Tests
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Development and validation of an offline deep learning algorithm to detect vitreoretinal abnormalities on ocular ultrasound.

Indian journal of ophthalmology Apr 1, 2022
PURPOSE: We describe our offline deep learning algorithm (DLA) and validation of its diagnostic ability to identify vitreoretinal abnormalities (VRA) on ocular ultrasound (OUS).
Sensitivity and Specificity Deep Learning ROC Curve Humans Eye Diseases Algorithms
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Multi-variable AUC for sifting complementary features and its biomedical application.

Briefings in bioinformatics Mar 10, 2022
Although sifting functional genes has been discussed for years, traditional selection methods tend to be ineffective in capturing potential specific genes. First, typical methods focus on finding features (genes) relevant to class while irrelevant to...
Algorithms Machine Learning ROC Curve Area Under Curve
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Adapt-Kcr: a novel deep learning framework for accurate prediction of lysine crotonylation sites based on learning embedding features and attention architecture.

Briefings in bioinformatics Mar 10, 2022
Protein lysine crotonylation (Kcr) is an important type of posttranslational modification that is associated with a wide range of biological processes. The identification of Kcr sites is critical to better understanding their functional mechanisms. H...
User-Computer Interface ROC Curve Computational Biology Protein Processing, Post-Translational Phosphorylation Databases, Factual Lysine Neural Networks, Computer Reproducibility of Results Software Deep Learning Algorithms
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Accelerating the discovery of antifungal peptides using deep temporal convolutional networks.

Briefings in bioinformatics Mar 10, 2022
The application of machine intelligence in biological sciences has led to the development of several automated tools, thus enabling rapid drug discovery. Adding to this development is the ongoing COVID-19 pandemic, due to which researchers working in...
Antimicrobial Peptides Reproducibility of Results Software Drug Discovery Humans Algorithms ROC Curve Deep Learning Databases, Factual Neural Networks, Computer Antifungal Agents Artificial Intelligence Workflow
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DEVELOPMENT AND VALIDATION OF AN EXPLAINABLE ARTIFICIAL INTELLIGENCE FRAMEWORK FOR MACULAR DISEASE DIAGNOSIS BASED ON OPTICAL COHERENCE TOMOGRAPHY IMAGES.

Retina (Philadelphia, Pa.) Mar 1, 2022
PURPOSE: To develop and validate an artificial intelligence framework for identifying multiple retinal lesions at image level and performing an explainable macular disease diagnosis at eye level in optical coherence tomography images.
Macular Edema Wet Macular Degeneration Geographic Atrophy Aged Adult Male Middle Aged ROC Curve Tomography, Optical Coherence Artificial Intelligence Retrospective Studies Female Humans Diabetic Retinopathy
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Machine Learning Used to Compare the Diagnostic Accuracy of Risk Factors, Clinical Signs and Biomarkers and to Develop a New Prediction Model for Neonatal Early-onset Sepsis.

The Pediatric infectious disease journal Mar 1, 2022
BACKGROUND: Current strategies for risk stratification and prediction of neonatal early-onset sepsis (EOS) are inefficient and lack diagnostic performance. The aim of this study was to use machine learning to analyze the diagnostic accuracy of risk f...
Humans Machine Learning Anti-Bacterial Agents Infant, Newborn Risk Factors Male Prospective Studies Biomarkers Female Neonatal Sepsis Infant ROC Curve C-Reactive Protein
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Comparison among Four Deep Learning Image Classification Algorithms in AI-based Diatom Test.

Fa yi xue za zhi Feb 25, 2022
OBJECTIVES: To select four algorithms with relatively balanced complexity and accuracy among deep learning image classification algorithms for automatic diatom recognition, and to explore the most suitable classification algorithm for diatom recognit...
Humans Deep Learning Neural Networks, Computer ROC Curve Algorithms Diatoms
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Comparison of Machine Learning Methods for Predicting Outcomes After In-Hospital Cardiac Arrest.

Critical care medicine Feb 1, 2022
OBJECTIVES: Prognostication of neurologic status among survivors of in-hospital cardiac arrests remains a challenging task for physicians. Although models such as the Cardiac Arrest Survival Post-Resuscitation In-hospital score are useful for predict...
ROC Curve Area Under Curve Outcome Assessment, Health Care Male Middle Aged Heart Arrest Humans Prognosis Cohort Studies Survivors Machine Learning Female Forecasting Aged
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