AIMC Topic: Predictive Value of Tests

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Past and present of computer-assisted dermoscopic diagnosis: performance of a conventional image analyser versus a convolutional neural network in a prospective data set of 1,981 skin lesions.

European journal of cancer (Oxford, England : 1990) Jun 10, 2020
BACKGROUND: Convolutional neural networks (CNNs) have shown a dermatologist-level performance in the classification of skin lesions. We aimed to deliver a head-to-head comparison of a conventional image analyser (CIA), which depends on segmentation a...
Adolescent Predictive Value of Tests Image Interpretation, Computer-Assisted Male Middle Aged Diagnosis, Computer-Assisted Deep Learning Female Melanoma Skin Neoplasms Dermoscopy Reproducibility of Results Aged Aged, 80 and over Young Adult Adult Cross-Sectional Studies Humans Databases, Factual Prospective Studies Prognosis
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A Framework for Effective Application of Machine Learning to Microbiome-Based Classification Problems.

mBio Jun 9, 2020
Machine learning (ML) modeling of the human microbiome has the potential to identify microbial biomarkers and aid in the diagnosis of many diseases such as inflammatory bowel disease, diabetes, and colorectal cancer. Progress has been made toward dev...
Feces Logistic Models RNA, Ribosomal, 16S Predictive Value of Tests Colonic Neoplasms Microbiota Linear Models Gastrointestinal Diseases Humans Machine Learning
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A novel model for predicting the outcome of intracerebral hemorrhage: Based on 1186 Patients.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Jun 8, 2020
OBJECTIVE: To establish a model for predicting the outcome according to the clinical and computed tomography(CT) image data of patients with intracerebral hemorrhage(ICH).
Humans Decision Support Techniques Prognosis Retrospective Studies Tomography, X-Ray Computed Female Risk Factors Male Middle Aged Risk Assessment Predictive Value of Tests China Time Factors Nomograms Support Vector Machine Cerebral Hemorrhage
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Defining heterogeneity of epicardial functional stenosis with low coronary flow reserve by unsupervised machine learning.

Heart and vessels Jun 6, 2020
Low CFR is associated with poor prognosis, whereas it is a heterogeneous condition according to the actual coronary flow, such as high resting or low hyperemic coronary flow, which should have different physiological traits and clinical implications....
Middle Aged Severity of Illness Index Diagnosis, Computer-Assisted Cluster Analysis Unsupervised Machine Learning Republic of Korea Female Aged Male Cardiac Catheterization Coronary Stenosis Fractional Flow Reserve, Myocardial Hyperemia Predictive Value of Tests Registries Japan Spain Blood Flow Velocity Humans Prognosis
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An innovative method for screening and evaluating the degree of diabetic retinopathy and drug treatment based on artificial intelligence algorithms.

Pharmacological research Jun 2, 2020
Current methods of evaluating the degree of diabetic retinopathy are highly subjective and have no quantitative standard. To objectively evaluate the slight changes in tissue structure during the early stage of retinal diseases, a subjective interpre...
Diabetic Retinopathy Predictive Value of Tests Drugs, Chinese Herbal Diabetes Mellitus, Experimental Retina Microscopy Image Interpretation, Computer-Assisted Early Diagnosis Retinal Ganglion Cells Pattern Recognition, Automated Retinal Vessels Animals Diabetes Mellitus, Type 2 Male Mice Severity of Illness Index Rats, Wistar Deep Learning Diabetes Mellitus, Type 1 Hypoglycemic Agents
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Machine-learning based MRI radiomics models for early detection of radiation-induced brain injury in nasopharyngeal carcinoma.

BMC cancer Jun 1, 2020
BACKGROUND: Early radiation-induced temporal lobe injury (RTLI) diagnosis in nasopharyngeal carcinoma (NPC) is clinically challenging, and prediction models of RTLI are lacking. Hence, we aimed to develop radiomic models for early detection of RTLI.
Adult Male Middle Aged ROC Curve Longitudinal Studies Humans Machine Learning Algorithms Retrospective Studies Female Image Interpretation, Computer-Assisted Radiation Injuries Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms Temporal Lobe Magnetic Resonance Imaging Brain Injuries Predictive Value of Tests Aftercare Models, Biological
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AD-NET: Age-adjust neural network for improved MCI to AD conversion prediction.

NeuroImage. Clinical Jun 1, 2020
The prediction of Mild Cognitive Impairment (MCI) patients who are at higher risk converting to Alzheimer's Disease (AD) is critical for effective intervention and patient selection in clinical trials. Different biomarkers including neuroimaging have...
Pattern Recognition, Automated Cognitive Dysfunction Neuroimaging Humans Age Factors Neural Networks, Computer Predictive Value of Tests Brain Alzheimer Disease Image Interpretation, Computer-Assisted Disease Progression
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Impact of machine learning-based coronary computed tomography angiography fractional flow reserve on treatment decisions and clinical outcomes in patients with suspected coronary artery disease.

European radiology May 28, 2020
OBJECTIVES: This study investigated the impact of machine learning (ML)-based fractional flow reserve derived from computed tomography (FFR) compared to invasive coronary angiography (ICA) for therapeutic decision-making and patient outcome in patien...
Machine Learning Disease Management Retrospective Studies Computed Tomography Angiography Severity of Illness Index Female Fractional Flow Reserve, Myocardial Humans Decision Making Male Artificial Intelligence Predictive Value of Tests Middle Aged Coronary Angiography Coronary Artery Disease
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A novel graph attention adversarial network for predicting disease-related associations.

Methods (San Diego, Calif.) May 21, 2020
Identifying complex human diseases at molecular level is very helpful, especially in diseases diagnosis, therapy, prognosis and monitoring. Accumulating evidences demonstrated that RNAs are playing important roles in identifying various complex human...
MicroRNAs RNA, Long Noncoding Predictive Value of Tests Datasets as Topic Deep Learning Gene Regulatory Networks Gene Expression Regulation Genetic Predisposition to Disease Genetic Association Studies Computational Biology Databases, Genetic
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Colour Doppler ultrasound of temporal arteries for the diagnosis of giant cell arteritis: a multicentre deep learning study.

Clinical and experimental rheumatology May 21, 2020
OBJECTIVES: Giant cell arteritis (GCA) is the most common systemic vasculitis in adults. In recent years, colour Doppler ultrasound of the temporal arteries (CDU) has proven to be a powerful non-invasive diagnostic tool, but its place in the diagnosi...
Giant Cell Arteritis Temporal Arteries Humans Algorithms Retrospective Studies Reproducibility of Results Sensitivity and Specificity Deep Learning Predictive Value of Tests Ultrasonography, Doppler, Color
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