AIMC Topic: Predictive Value of Tests

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Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs.

JAMA ophthalmology Dec 1, 2019
IMPORTANCE: A deep learning system (DLS) that could automatically detect glaucomatous optic neuropathy (GON) with high sensitivity and specificity could expedite screening for GON.
Humans Databases, Factual Female Optic Nerve Diseases False Positive Reactions Diagnostic Techniques, Ophthalmological Photography Glaucoma, Open-Angle ROC Curve Predictive Value of Tests Area Under Curve Fundus Oculi Sensitivity and Specificity Cross-Sectional Studies Male Deep Learning
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OPTICAL COHERENCE TOMOGRAPHY BIOMARKERS TO DISTINGUISH DIABETIC MACULAR EDEMA FROM PSEUDOPHAKIC CYSTOID MACULAR EDEMA USING MACHINE LEARNING ALGORITHMS.

Retina (Philadelphia, Pa.) Dec 1, 2019
PURPOSE: In diabetic patients presenting with macular edema (ME) shortly after cataract surgery, identifying the underlying pathology can be challenging and influence management. Our aim was to develop a simple clinical classifier able to confirm a d...
Aged Sensitivity and Specificity Male Middle Aged Biomarkers Retrospective Studies Female Reproducibility of Results Tomography, Optical Coherence Macular Edema Fluorescein Angiography Humans Subretinal Fluid Diabetic Retinopathy Pseudophakia Machine Learning Diagnosis, Computer-Assisted Visual Acuity Predictive Value of Tests Area Under Curve
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Development and Validation of a Machine Learning Algorithm for Predicting Response to Anticholinergic Medications for Overactive Bladder Syndrome.

Obstetrics and gynecology Nov 1, 2019
OBJECTIVE: To develop and externally validate a prediction model for anticholinergic response in patients with overactive bladder (OAB).
Urinary Bladder, Overactive Urinary Incontinence Cholinergic Antagonists Adult Middle Aged Predictive Value of Tests Area Under Curve Humans Machine Learning Algorithms Prognosis Female Reproducibility of Results Aged
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What Are the Applications and Limitations of Artificial Intelligence for Fracture Detection and Classification in Orthopaedic Trauma Imaging? A Systematic Review.

Clinical orthopaedics and related research Nov 1, 2019
BACKGROUND: Artificial-intelligence algorithms derive rules and patterns from large amounts of data to calculate the probabilities of various outcomes using new sets of similar data. In medicine, artificial intelligence (AI) has been applied primaril...
Humans Predictive Value of Tests Orthopedics Artificial Intelligence Algorithms ROC Curve Fractures, Bone
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Histogram analysis of absolute cerebral blood volume map can distinguish glioblastoma from solitary brain metastasis.

Medicine Oct 1, 2019
Glioblastoma multiforme (GBM) is difficult to be separated from solitary brain metastasis (sBM) in clinical practice. This study aimed to distinguish two entities by the histogram analysis of absolute cerebral blood volume (CBV) map.From March 2016 t...
ROC Curve Diagnosis, Differential Predictive Value of Tests Aged Glioblastoma Image Interpretation, Computer-Assisted Humans Brain Neoplasms Cerebral Blood Volume Machine Learning Male Retrospective Studies Middle Aged Female
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Computational pathology and the understanding of disease.

The Journal of pathology Oct 1, 2019
Image Interpretation, Computer-Assisted Pathology Editorial Policies Humans Diagnosis, Computer-Assisted Artificial Intelligence Predictive Value of Tests Periodicals as Topic
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Outcome Prediction in Postanoxic Coma With Deep Learning.

Critical care medicine Oct 1, 2019
OBJECTIVES: Visual assessment of the electroencephalogram by experienced clinical neurophysiologists allows reliable outcome prediction of approximately half of all comatose patients after cardiac arrest. Deep neural networks hold promise to achieve ...
Deep Learning Predictive Value of Tests Electroencephalography Heart Arrest Coma Hypoxia, Brain Female Aged Male Middle Aged Humans Prospective Studies
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Predicting 90-Day and 1-Year Mortality in Spinal Metastatic Disease: Development and Internal Validation.

Neurosurgery Oct 1, 2019
BACKGROUND: Increasing prevalence of metastatic disease has been accompanied by increasing rates of surgical intervention. Current tools have poor to fair predictive performance for intermediate (90-d) and long-term (1-yr) mortality.
Humans Neural Networks, Computer Middle Aged Time Factors Predictive Value of Tests Reproducibility of Results Spinal Neoplasms Machine Learning Aged Algorithms Survival Rate Retrospective Studies Male Female
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Prior to Initiation of Chemotherapy, Can We Predict Breast Tumor Response? Deep Learning Convolutional Neural Networks Approach Using a Breast MRI Tumor Dataset.

Journal of digital imaging Oct 1, 2019
We hypothesize that convolutional neural networks (CNN) can be used to predict neoadjuvant chemotherapy (NAC) response using a breast MRI tumor dataset prior to initiation of chemotherapy. An institutional review board-approved retrospective review o...
Datasets as Topic Magnetic Resonance Imaging Predictive Value of Tests Breast Algorithms Sensitivity and Specificity Image Interpretation, Computer-Assisted Retrospective Studies Breast Neoplasms Humans Female Deep Learning Neural Networks, Computer Treatment Outcome
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Optical Coherence Tomography Vulnerable Plaque Segmentation Based on Deep Residual U-Net.

Reviews in cardiovascular medicine Sep 30, 2019
Automatic and accurate segmentation of intravascular optical coherence tomography imagery is of great importance in computer-aided diagnosis and in treatment of cardiovascular diseases. However, this task has not been well addressed for two reasons. ...
Coronary Vessels Rupture, Spontaneous Plaque, Atherosclerotic Entropy Humans Predictive Value of Tests Prognosis Tomography, Optical Coherence Reproducibility of Results Coronary Artery Disease Deep Learning Image Interpretation, Computer-Assisted
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