AI Medical Compendium Topic:
Diagnosis, Computer-Assisted

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Separability of Acute Cerebral Infarction Lesions in CT Based Radiomics: Toward Artificial Intelligence-Assisted Diagnosis.

BioMed research international Nov 15, 2020
This study aims at analyzing the separability of acute cerebral infarction lesions which were invisible in CT. 38 patients, who were diagnosed with acute cerebral infarction and performed both CT and MRI, and 18 patients, who had no positive finding ...
Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Female Acute Disease Adult Male Cerebral Infarction Humans Middle Aged Artificial Intelligence Algorithms Tomography, X-Ray Computed
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Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: a 500 participants study.

The international journal of cardiovascular imaging Nov 12, 2020
Machine learning (ML)-based algorithms for cardiovascular disease (CVD) risk assessment have shown promise in clinical decisions. However, they usually predict binary events using only conventional risk factors. Our overall goal was to develop the "m...
Decision Support Techniques Prognosis Female Reproducibility of Results Aged Plaque, Atherosclerotic Diagnosis, Computer-Assisted Carotid Stenosis Pilot Projects Humans Coronary Stenosis Ultrasonography Machine Learning Support Vector Machine Coronary Angiography Predictive Value of Tests Cross-Sectional Studies Radiographic Image Interpretation, Computer-Assisted Male Stroke Middle Aged Heart Disease Risk Factors Risk Assessment
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Recent Advances in Medical Image Processing.

Acta cytologica Nov 11, 2020
BACKGROUND: Application and development of the artificial intelligence technology have generated a profound impact in the field of medical imaging. It helps medical personnel to make an early and more accurate diagnosis. Recently, the deep convolutio...
Predictive Value of Tests Image Interpretation, Computer-Assisted Neural Networks, Computer Reproducibility of Results Diagnosis, Computer-Assisted Deep Learning Humans
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Neural Network Vessel Lumen Regression for Automated Lumen Cross-Section Segmentation in Cardiovascular Image-Based Modeling.

Cardiovascular engineering and technology Nov 11, 2020
PURPOSE: We accelerate a pathline-based cardiovascular model building method by training machine learning models to directly predict vessel lumen surface points from computed tomography (CT) and magnetic resonance (MR) medical image data.
Neural Networks, Computer Reproducibility of Results Diagnosis, Computer-Assisted Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Automation Magnetic Resonance Angiography Computed Tomography Angiography Models, Cardiovascular Humans Patient-Specific Modeling Blood Vessels
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Predictive modeling of proliferative vitreoretinopathy using automated machine learning by ophthalmologists without coding experience.

Scientific reports Nov 11, 2020
We aimed to assess the feasibility of machine learning (ML) algorithm design to predict proliferative vitreoretinopathy (PVR) by ophthalmologists without coding experience using automated ML (AutoML). The study was a retrospective cohort study of 506...
Male Middle Aged Postoperative Complications Diagnosis, Computer-Assisted Vitrectomy Algorithms Ophthalmologists Retinal Detachment Retrospective Studies Humans Vitreoretinopathy, Proliferative Machine Learning Female Risk Factors Aged
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Machine Learned Cellular Phenotypes in Cardiomyopathy Predict Sudden Death.

Circulation research Nov 10, 2020
RATIONALE: Susceptibility to VT/VF (ventricular tachycardia/fibrillation) is difficult to predict in patients with ischemic cardiomyopathy either by clinical tools or by attempting to translate cellular mechanisms to the bedside.
Action Potentials Predictive Value of Tests Signal Processing, Computer-Assisted Myocardial Infarction Tachycardia, Ventricular Risk Assessment Diagnosis, Computer-Assisted Time Factors Support Vector Machine Cardiomyopathies Ventricular Fibrillation Death, Sudden, Cardiac Electrophysiologic Techniques, Cardiac Phenotype Prospective Studies Prognosis Female Risk Factors Aged Aged, 80 and over Male Middle Aged Humans Neural Networks, Computer
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CheXLocNet: Automatic localization of pneumothorax in chest radiographs using deep convolutional neural networks.

PloS one Nov 9, 2020
BACKGROUND: Pneumothorax can lead to a life-threatening emergency. The experienced radiologists can offer precise diagnosis according to the chest radiographs. The localization of the pneumothorax lesions will help to quickly diagnose, which will be ...
Radiography Pneumothorax Humans Neural Networks, Computer Diagnosis, Computer-Assisted Deep Learning Image Processing, Computer-Assisted
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Deep Learning-Based Segmentation and Quantification in Experimental Kidney Histopathology.

Journal of the American Society of Nephrology : JASN Nov 5, 2020
BACKGROUND: Nephropathologic analyses provide important outcomes-related data in experiments with the animal models that are essential for understanding kidney disease pathophysiology. Precision medicine increases the demand for quantitative, unbiase...
Translational Research, Biomedical Diagnosis, Computer-Assisted Schiff Bases Pattern Recognition, Automated Deep Learning Periodic Acid Image Processing, Computer-Assisted Mice Kidney Disease Models, Animal Algorithms Mice, Inbred C57BL Neural Networks, Computer Reproducibility of Results Kidney Diseases Animals Kidney Glomerulus Male
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Cumulative learning enables convolutional neural network representations for small mass spectrometry data classification.

Nature communications Nov 5, 2020
Rapid and accurate clinical diagnosis remains challenging. A component of diagnosis tool development is the design of effective classification models with Mass spectrometry (MS) data. Some Machine Learning approaches have been investigated but these ...
Humans Neural Networks, Computer Machine Learning Databases, Factual Animals Diagnosis, Computer-Assisted Deep Learning Mass Spectrometry
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Predictive diagnosis of chronic obstructive pulmonary disease using serum metabolic biomarkers and least-squares support vector machine.

Journal of clinical laboratory analysis Nov 3, 2020
OBJECTIVE: Development of biofluid-based biomarkers is attractive for the diagnosis of chronic obstructive pulmonary disease (COPD) but still lacking. Thus, here we aimed to identify serum metabolic biomarkers for the diagnosis of COPD.
Humans Artificial Intelligence Biomarkers Female Aged Diagnosis, Computer-Assisted Support Vector Machine Metabolomics Least-Squares Analysis Magnetic Resonance Spectroscopy Pulmonary Disease, Chronic Obstructive Male Middle Aged Case-Control Studies
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