AIMC Topic: ROC Curve

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Routine Laboratory Blood Tests Predict SARS-CoV-2 Infection Using Machine Learning.

Clinical chemistry Nov 1, 2020
BACKGROUND: Accurate diagnostic strategies to identify SARS-CoV-2 positive individuals rapidly for management of patient care and protection of health care personnel are urgently needed. The predominant diagnostic test is viral RNA detection by RT-PC...
Female Aged Young Adult Adult Male Humans Machine Learning Pandemics COVID-19 Middle Aged Retrospective Studies Reverse Transcriptase Polymerase Chain Reaction ROC Curve COVID-19 Testing Models, Theoretical Laboratories Coronavirus Infections Hematologic Tests Clinical Laboratory Techniques Pneumonia, Viral
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DeepRMethylSite: a deep learning based approach for prediction of arginine methylation sites in proteins.

Molecular omics Oct 12, 2020
Methylation, which is one of the most prominent post-translational modifications on proteins, regulates many important cellular functions. Though several model-based methylation site predictors have been reported, all existing methods employ machine ...
Databases, Protein Methylation Arginine Neural Networks, Computer Reproducibility of Results Algorithms Deep Learning ROC Curve Protein Processing, Post-Translational Proteins
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Prediction of systemic biomarkers from retinal photographs: development and validation of deep-learning algorithms.

The Lancet. Digital health Oct 1, 2020
BACKGROUND: The application of deep learning to retinal photographs has yielded promising results in predicting age, sex, blood pressure, and haematological parameters. However, the broader applicability of retinal photograph-based deep learning for ...
ROC Curve Image Processing, Computer-Assisted Europe Area Under Curve Singapore Female Male Middle Aged Deep Learning United Kingdom Beijing Asia Humans Photography Neural Networks, Computer Body Composition Muscles Algorithms Models, Biological Biomarkers Creatinine Republic of Korea Retina Ethnicity
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Use of word and graph embedding to measure semantic relatedness between Unified Medical Language System concepts.

Journal of the American Medical Informatics Association : JAMIA Oct 1, 2020
OBJECTIVE: The study sought to explore the use of deep learning techniques to measure the semantic relatedness between Unified Medical Language System (UMLS) concepts.
Medical Subject Headings Terminology as Topic Unified Medical Language System Deep Learning ROC Curve Natural Language Processing Semantics
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Low-Shot Deep Learning of Diabetic Retinopathy With Potential Applications to Address Artificial Intelligence Bias in Retinal Diagnostics and Rare Ophthalmic Diseases.

JAMA ophthalmology Oct 1, 2020
IMPORTANCE: Recent studies have demonstrated the successful application of artificial intelligence (AI) for automated retinal disease diagnostics but have not addressed a fundamental challenge for deep learning systems: the current need for large, cr...
Neural Networks, Computer Artificial Intelligence Algorithms Retrospective Studies Female Cross-Sectional Studies Male Deep Learning ROC Curve Rare Diseases Humans Diabetic Retinopathy
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A statistically rigorous deep neural network approach to predict mortality in trauma patients admitted to the intensive care unit.

The journal of trauma and acute care surgery Oct 1, 2020
BACKGROUND: Trauma patients admitted to critical care are at high risk of mortality because of their injuries. Our aim was to develop a machine learning-based model to predict mortality using Fahad-Liaqat-Ahmad Intensive Machine (FLAIM) framework. We...
Adult Male Organ Dysfunction Scores Middle Aged Critical Illness Wounds and Injuries Sodium Sepsis Humans Intensive Care Units Critical Care ROC Curve Neural Networks, Computer Female Proportional Hazards Models Machine Learning Hospitalization Multivariate Analysis Prognosis Injury Severity Score Retrospective Studies Young Adult
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Explainable Machine Learning Model for Predicting GI Bleed Mortality in the Intensive Care Unit.

The American journal of gastroenterology Oct 1, 2020
INTRODUCTION: Acute gastrointestinal (GI) bleed is a common reason for hospitalization with 2%-10% risk of mortality. In this study, we developed a machine learning (ML) model to calculate the risk of mortality in intensive care unit patients admitte...
APACHE Gastrointestinal Hemorrhage Middle Aged Risk Assessment ROC Curve Area Under Curve Humans Machine Learning Intensive Care Units Female Aged Aged, 80 and over Male
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Using deep-learning algorithms to classify fetal brain ultrasound images as normal or abnormal.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology Oct 1, 2020
OBJECTIVES: To evaluate the feasibility of using deep-learning algorithms to classify as normal or abnormal sonographic images of the fetal brain obtained in standard axial planes.
Humans Brain Pregnancy Image Processing, Computer-Assisted Diagnosis, Differential Feasibility Studies Fetus Nervous System Malformations Female Sensitivity and Specificity Ultrasonography, Prenatal Deep Learning ROC Curve
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Development and validation of a machine-learning model for prediction of shoulder dystocia.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology Oct 1, 2020
OBJECTIVES: To develop a machine-learning (ML) model for prediction of shoulder dystocia (ShD) and to externally validate the model's predictive accuracy and potential clinical efficacy in optimizing the use of Cesarean delivery in the context of sus...
ROC Curve Predictive Value of Tests Patient Selection Humans Israel Cesarean Section Machine Learning Diabetes, Gestational Pregnancy Reproducibility of Results Female Gestational Age Risk Factors Adult Biometry Ultrasonography, Prenatal Fetal Weight Fetal Macrosomia Shoulder Dystocia
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Leveraging Machine Learning to Identify Predictors of Receiving Psychosocial Treatment for Attention Deficit/Hyperactivity Disorder.

Administration and policy in mental health Sep 1, 2020
This study aimed to identify factors associated with receiving psychosocial treatment for ADHD in a nationally representative sample. Participants were 6630 youth with a parent-reported diagnosis of ADHD from the 2016-2017 National Survey of Children...
Child ROC Curve Male Socioeconomic Factors Attention Deficit Disorder with Hyperactivity Comorbidity Humans Patient Acceptance of Health Care Severity of Illness Index Machine Learning Adolescent Female Child, Preschool Risk Factors
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