AIMC Topic: Sensitivity and Specificity

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Morphogo: An Automatic Bone Marrow Cell Classification System on Digital Images Analyzed by Artificial Intelligence.

Acta cytologica Jul 28, 2020
INTRODUCTION: The nucleated-cell differential count on the bone marrow aspirate smears is required for the clinical diagnosis of hematological malignancy. Manual bone marrow differential count is time consuming and lacks consistency. In this study, a...
Bone Marrow Cells Sensitivity and Specificity Leukocyte Count Hematologic Neoplasms Humans Pilot Projects Artificial Intelligence Bone Marrow Algorithms
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Deep Learning Approach for Anterior Cruciate Ligament Lesion Detection: Evaluation of Diagnostic Performance Using Arthroscopy as the Reference Standard.

Journal of magnetic resonance imaging : JMRI Jul 26, 2020
BACKGROUND: MRI is the most commonly used imaging method for diagnosing anterior cruciate ligament (ACL) injuries. However, the interpretation of knee MRI is time-intensive and depends on the clinical experience of the reader. An automated detection ...
Humans Retrospective Studies Reproducibility of Results Sensitivity and Specificity Deep Learning Magnetic Resonance Imaging Arthroscopy Reference Standards Anterior Cruciate Ligament Injuries Anterior Cruciate Ligament
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An automated detection system for colonoscopy images using a dual encoder-decoder model.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jul 26, 2020
Conventional computer-aided detection systems (CADs) for colonoscopic images utilize shape, texture, or temporal information to detect polyps, so they have limited sensitivity and specificity. This study proposes a method to extract possible polyp fe...
Humans Neural Networks, Computer Sensitivity and Specificity Colonoscopy Image Processing, Computer-Assisted
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Economic Challenges of Artificial Intelligence Adoption for Diabetic Retinopathy.

Ophthalmology Jul 25, 2020
Reimbursement Mechanisms Humans United States Diabetic Retinopathy Ophthalmology Artificial Intelligence Medicare Sensitivity and Specificity Diagnostic Techniques, Ophthalmological
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Preoperative prediction for pathological grade of hepatocellular carcinoma via machine learning-based radiomics.

European radiology Jul 22, 2020
OBJECTIVE: To investigate the efficacy of contrast-enhanced computed tomography (CECT)-based radiomics signatures for preoperative prediction of pathological grades of hepatocellular carcinoma (HCC) via machine learning.
Reproducibility of Results Area Under Curve Liver Neoplasms Aged Carcinoma, Hepatocellular Humans Machine Learning Male Image Processing, Computer-Assisted Adult Retrospective Studies Middle Aged Sensitivity and Specificity Tomography, X-Ray Computed Diagnosis, Computer-Assisted Female ROC Curve
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Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning.

Medical image analysis Jul 21, 2020
The COVID-19 pandemic is causing a major outbreak in more than 150 countries around the world, having a severe impact on the health and life of many people globally. One of the crucial step in fighting COVID-19 is the ability to detect the infected p...
Radiography, Thoracic Sensitivity and Specificity Humans Neural Networks, Computer Data Interpretation, Statistical Pandemics Radiographic Image Interpretation, Computer-Assisted COVID-19 Coronavirus Infections SARS-CoV-2 Datasets as Topic Deep Learning Diagnosis, Differential Predictive Value of Tests Betacoronavirus Pneumonia, Viral
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Machine learning-based prediction of persistent oppositional defiant behavior for 5 years.

Nordic journal of psychiatry Jul 20, 2020
BACKGROUND: Early detection of oppositional defiant behavior is warranted for timely intervention in children at risk. This study aimed to build a predictive model of persistent oppositional defiant behavior based on a machine learning algorithm.
Cohort Studies Child, Preschool Child Attention Deficit and Disruptive Behavior Disorders Humans Machine Learning Sensitivity and Specificity
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Feed-forward neural networks using cerebral MR spectroscopy and DTI might predict neurodevelopmental outcome in preterm neonates.

European radiology Jul 18, 2020
OBJECTIVES: We aimed to evaluate the ability of feed-forward neural networks (fNNs) to predict the neurodevelopmental outcome (NDO) of very preterm neonates (VPIs) at 12 months corrected age by using biomarkers of cerebral MR proton spectroscopy (H-M...
Male Infant Predictive Value of Tests Image Interpretation, Computer-Assisted Prognosis Female Infant, Newborn Sensitivity and Specificity Infant, Premature, Diseases Infant, Premature Developmental Disabilities Magnetic Resonance Spectroscopy Diffusion Tensor Imaging Humans Neural Networks, Computer Prospective Studies Brain
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Structure equation model and neural network analyses to predict coronary artery lesions in Kawasaki disease: a single-centre retrospective study.

Scientific reports Jul 17, 2020
A new method to predict coronary artery lesions (CALs) in Kawasaki disease (KD) was developed using a mean structure equation model (SEM) and neural networks (Nnet). There were 314 admitted children with KD who met at least four of the six diagnostic...
Humans Neural Networks, Computer Biomarkers Mucocutaneous Lymph Node Syndrome Coronary Artery Disease Adult Disease Susceptibility Sensitivity and Specificity Prognosis Male Retrospective Studies Models, Statistical Female
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A fully automated artificial intelligence method for non-invasive, imaging-based identification of genetic alterations in glioblastomas.

Scientific reports Jul 16, 2020
Glioblastoma is the most common malignant brain parenchymal tumor yet remains challenging to treat. The current standard of care-resection and chemoradiation-is limited in part due to the genetic heterogeneity of glioblastoma. Previous studies have i...
Cyclin-Dependent Kinase Inhibitor p16 Decision Trees Glioblastoma Gene Expression Humans Biomarkers, Tumor Artificial Intelligence Brain Neoplasms Preoperative Care Mutation Male Retrospective Studies Chromosomes, Human, Pair 10 Aneuploidy Magnetic Resonance Imaging Chromosomes, Human, Pair 7 Female Image Interpretation, Computer-Assisted X-linked Nuclear Protein Sensitivity and Specificity Isocitrate Dehydrogenase
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