AIMC Journal:
Academic radiology

Showing 241 to 250 of 317 articles

Transparent Machine Learning Models to Diagnose Suspicious Thoracic Lesions Leveraging CT Guided Biopsy Data.

Academic radiology Aug 7, 2021
RATIONALE AND OBJECTIVES: To train and validate machine learning models capable of classifying suspicious thoracic lesions as benign or malignant and to further classify malignant lesions by pathologic subtype while quantifying feature importance for...
Image-Guided Biopsy Multiparametric Magnetic Resonance Imaging Retrospective Studies Tomography, X-Ray Computed Humans Machine Learning
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BERT for the Processing of Radiological Reports: An Attention-based Natural Language Processing Algorithm.

Academic radiology Aug 4, 2021
Natural Language Processing Radiography Humans Radiology Algorithms
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Artificial Intelligence for Interstitial Lung Disease Analysis on Chest Computed Tomography: A Systematic Review.

Academic radiology Jul 1, 2021
RATIONALE AND OBJECTIVES: High-resolution computed tomography (HRCT) is paramount in the assessment of interstitial lung disease (ILD). Yet, HRCT interpretation of ILDs may be hampered by inter- and intra-observer variability. Recently, artificial in...
Humans Lung Lung Diseases, Interstitial Retrospective Studies Tomography, X-Ray Computed Artificial Intelligence Prospective Studies
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Weakly Supervised Deep Learning Approach to Breast MRI Assessment.

Academic radiology Jun 6, 2021
RATIONALE AND OBJECTIVES: To evaluate a weakly supervised deep learning approach to breast Magnetic Resonance Imaging (MRI) assessment without pixel level segmentation in order to improve the specificity of breast MRI lesion classification.
Female Sensitivity and Specificity Humans Magnetic Resonance Imaging Breast Breast Neoplasms Deep Learning
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Predicting Prolonged Hospitalization and Supplemental Oxygenation in Patients with COVID-19 Infection from Ambulatory Chest Radiographs using Deep Learning.

Academic radiology May 21, 2021
RATIONALE AND OBJECTIVES: The clinical prognosis of outpatients with coronavirus disease 2019 (COVID-19) remains difficult to predict, with outcomes including asymptomatic, hospitalization, intubation, and death. Here we determined the prognostic val...
Oxygen Radiography, Thoracic Middle Aged Deep Learning Retrospective Studies Female Adult Hospitalization Humans Male COVID-19
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Quantitative Imaging of Body Fat Distribution in the Era of Deep Learning.

Academic radiology May 19, 2021
Body Fat Distribution Humans Deep Learning Image Processing, Computer-Assisted Diagnostic Imaging
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Review of Artificial Intelligence Training Tools and Courses for Radiologists.

Academic radiology Mar 11, 2021
Artificial intelligence (AI) systems play an increasingly important role in all parts of the imaging chain, from image creation to image interpretation to report generation. In order to responsibly manage radiology AI systems and make informed purcha...
Humans Artificial Intelligence Radiography Radiology Radiologists
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Quantification of COVID-19 Opacities on Chest CT - Evaluation of a Fully Automatic AI-approach to Noninvasively Differentiate Critical Versus Noncritical Patients.

Academic radiology Mar 6, 2021
OBJECTIVES: To evaluate the potential of a fully automatic artificial intelligence (AI)-driven computed tomography (CT) software prototype to quantify severity of COVID-19 infection on chest CT in relationship with clinical and laboratory data.
Lung Tomography, X-Ray Computed Middle Aged COVID-19 Retrospective Studies Humans Artificial Intelligence
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Diagnostic Imaging and Mechanical Objectivity in Medicine.

Academic radiology Jan 20, 2021
BACKGROUND: Before the advent of automatism in image-making practices, scientists, anatomists, and physicians artistically depicted simplified images for scientific atlas making. This technique conferred subjectivity to a supposedly objective scienti...
Data Collection Bibliometrics Diagnostic Imaging Humans Artificial Intelligence
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Multi-Radiologist User Study for Artificial Intelligence-Guided Grading of COVID-19 Lung Disease Severity on Chest Radiographs.

Academic radiology Jan 18, 2021
RATIONALE AND OBJECTIVES: Radiographic findings of COVID-19 pneumonia can be used for patient risk stratification; however, radiologist reporting of disease severity is inconsistent on chest radiographs (CXRs). We aimed to see if an artificial intell...
Lung Retrospective Studies Severity of Illness Index Artificial Intelligence Humans Radiologists SARS-CoV-2 COVID-19 Radiography, Thoracic
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