AIMC Topic: Sensitivity and Specificity

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Evaluation of acute pulmonary embolism and clot burden on CTPA with deep learning.

European radiology Feb 16, 2020
OBJECTIVES: To take advantage of the deep learning algorithms to detect and calculate clot burden of acute pulmonary embolism (APE) on computed tomographic pulmonary angiography (CTPA).
Pulmonary Embolism Heart Ventricles Computed Tomography Angiography Ventricular Function, Right Male Humans Aged Middle Aged Retrospective Studies Adult Deep Learning Female Sensitivity and Specificity Acute Disease Reproducibility of Results
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Diagnosing chronic atrophic gastritis by gastroscopy using artificial intelligence.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver Feb 13, 2020
BACKGROUND: The sensitivity of endoscopy in diagnosing chronic atrophic gastritis is only 42%, and multipoint biopsy, despite being more accurate, is not always available.
Image Processing, Computer-Assisted Gastroscopy Humans Sensitivity and Specificity Gastritis, Atrophic Aged Neural Networks, Computer Male Adult Artificial Intelligence Middle Aged Stomach Neoplasms Female China
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Deep learning for automated cerebral aneurysm detection on computed tomography images.

International journal of computer assisted radiology and surgery Feb 13, 2020
PURPOSE: Cerebrovascular aneurysms are being observed with rapidly increasing incidence. Therefore, tools are needed for accurate and efficient detection of aneurysms. We used deep learning techniques with CT angiography acquired from multiple medica...
Image Processing, Computer-Assisted Cerebral Angiography Intracranial Aneurysm Humans Databases, Factual Tomography, X-Ray Computed Sensitivity and Specificity Deep Learning
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Discriminating progressive supranuclear palsy from Parkinson's disease using wearable technology and machine learning.

Gait & posture Feb 10, 2020
BACKGROUND: Progressive supranuclear palsy (PSP), a neurodegenerative conditions may be difficult to discriminate clinically from idiopathic Parkinson's disease (PD). It is critical that we are able to do this accurately and as early as possible in o...
Male Middle Aged Wearable Electronic Devices Logistic Models Humans Parkinson Disease Machine Learning Aged Algorithms Diagnosis, Differential Aged, 80 and over Female Gait Analysis Sensitivity and Specificity Supranuclear Palsy, Progressive
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The Prediction of Human Abdominal Adiposity Based on the Combination of a Particle Swarm Algorithm and Support Vector Machine.

International journal of environmental research and public health Feb 10, 2020
: Abdominal adiposity is an important risk factor of chronic cardiovascular diseases, thus the prediction of abdominal adiposity and obesity can reduce the risks of contracting such diseases. However, the current prediction models display low accurac...
Obesity, Abdominal Sensitivity and Specificity Humans Diagnosis, Computer-Assisted Adiposity Algorithms Support Vector Machine Risk Factors Predictive Value of Tests
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DMENet: Diabetic Macular Edema diagnosis using Hierarchical Ensemble of CNNs.

PloS one Feb 10, 2020
UNLABELLED: Diabetic Macular Edema (DME) is an advanced stage of Diabetic Retinopathy (DR) and can lead to permanent vision loss. Currently, it affects 26.7 million people globally and on account of such a huge number of DME cases and the limited num...
Macular Edema Algorithms Humans Sensitivity and Specificity Diabetic Retinopathy Datasets as Topic Diagnosis, Computer-Assisted Neural Networks, Computer Early Diagnosis Deep Learning
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QuPWM: Feature Extraction Method for Epileptic Spike Classification.

IEEE journal of biomedical and health informatics Feb 7, 2020
Epilepsy is a neurological disorder ranked as the second most serious neurological disease known to humanity, after stroke. Inter-ictal spiking is an abnormal neuronal discharge after an epileptic seizure. This abnormal activity can originate from on...
Sensitivity and Specificity Electroencephalography Epilepsy Signal Processing, Computer-Assisted Humans Machine Learning Algorithms Brain
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Better efficacy in differentiating WHO grade II from III oligodendrogliomas with machine-learning than radiologist's reading from conventional T1 contrast-enhanced and fluid attenuated inversion recovery images.

BMC neurology Feb 7, 2020
BACKGROUND: The medical imaging to differentiate World Health Organization (WHO) grade II (ODG2) from III (ODG3) oligodendrogliomas still remains a challenge. We investigated whether combination of machine leaning with radiomics from conventional T1 ...
Radiologists World Health Organization Oligodendroglioma Adolescent Child Magnetic Resonance Imaging Female Aged Young Adult Adult Sensitivity and Specificity Male Middle Aged Humans Machine Learning Algorithms Retrospective Studies
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A machine learning approach for handling big data produced by high resolution mass spectrometry after data independent acquisition of small molecules - Proof of concept study using an artificial neural network for sample classification.

Drug testing and analysis Feb 6, 2020
Liquid chromatography coupled to high-resolution mass spectrometry (HRMS) enables data independent acquisition (DIA) and untargeted screening. However, to avoid the handling of the resulting large dataset, most laboratories in that field still use ta...
Proof of Concept Study Small Molecule Libraries Cocaine Zolpidem Mass Spectrometry Chromatography, Liquid Substance Abuse Detection Humans Neural Networks, Computer Machine Learning Reproducibility of Results Sensitivity and Specificity Big Data
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Accuracy of a machine learning muscle MRI-based tool for the diagnosis of muscular dystrophies.

Neurology Feb 6, 2020
OBJECTIVE: Genetic diagnosis of muscular dystrophies (MDs) has classically been guided by clinical presentation, muscle biopsy, and muscle MRI data. Muscle MRI suggests diagnosis based on the pattern of muscle fatty replacement. However, patterns ove...
Humans Magnetic Resonance Imaging Muscle, Skeletal Supervised Machine Learning Muscular Dystrophies Reproducibility of Results Adult Sensitivity and Specificity Models, Theoretical
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