AIMC Topic: Feasibility Studies

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Diagnostic Accuracies of Laryngeal Diseases Using a Convolutional Neural Network-Based Image Classification System.

The Laryngoscope May 17, 2021
OBJECTIVES/HYPOTHESIS: There may be an interobserver variation in the diagnosis of laryngeal disease based on laryngoscopic images according to clinical experience. Therefore, this study is aimed to perform computer-assisted diagnosis for common lary...
Image Interpretation, Computer-Assisted Datasets as Topic Laryngoscopy Laryngeal Diseases Deep Learning ROC Curve Predictive Value of Tests Feasibility Studies Larynx Humans Retrospective Studies
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Generative adversarial network for glioblastoma ensures morphologic variations and improves diagnostic model for isocitrate dehydrogenase mutant type.

Scientific reports May 10, 2021
Generative adversarial network (GAN) creates synthetic images to increase data quantity, but whether GAN ensures meaningful morphologic variations is still unknown. We investigated whether GAN-based synthetic images provide sufficient morphologic var...
Female Aged Adult Brain Neoplasms Humans Brain Retrospective Studies Datasets as Topic Male DNA Mutational Analysis Middle Aged Isocitrate Dehydrogenase Deep Learning Magnetic Resonance Imaging Contrast Media Glioblastoma Feasibility Studies Image Interpretation, Computer-Assisted
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Feasibility of high-resolution magnetic resonance imaging of the liver using deep learning reconstruction based on the deep learning denoising technique.

Magnetic resonance imaging May 7, 2021
PURPOSE: To evaluate the feasibility of High-resolution (HR) magnetic resonance imaging (MRI) of the liver using deep learning reconstruction (DLR) based on a deep learning denoising technique compared with standard-resolution (SR) imaging.
Signal-To-Noise Ratio Humans Magnetic Resonance Imaging Liver Retrospective Studies Radiographic Image Interpretation, Computer-Assisted Female Feasibility Studies Aged Deep Learning
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Decoding the microstructural properties of white matter using realistic models.

NeuroImage May 5, 2021
Multi-echo gradient echo (ME-GRE) magnetic resonance signal evolution in white matter has a strong dependence on the orientation of myelinated axons with respect to the main static field. Although analytical solutions have been able to predict some o...
Humans Computer Simulation Female Feasibility Studies Autopsy Neuroimaging Microscopy, Electron White Matter Aged, 80 and over Deep Learning Models, Theoretical Magnetic Resonance Imaging
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Prediction of brain age from routine T2-weighted spin-echo brain magnetic resonance images with a deep convolutional neural network.

Neurobiology of aging Apr 28, 2021
Our study investigated the feasibility and clinical relevance of brain age prediction using axial T2-weighted images (T2-WIs) with a deep convolutional neural network (CNN) algorithm. The CNN model was trained by 1,530 scans in our institution. The p...
Feasibility Studies Neuroimaging Humans Middle Aged White Matter Aged Neural Networks, Computer Diffusion Magnetic Resonance Imaging Deep Learning Adult Brain Diabetes Mellitus Male Female Predictive Value of Tests Aging
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Feasibility of deep learning-based fully automated classification of microsatellite instability in tissue slides of colorectal cancer.

International journal of cancer Apr 27, 2021
High levels of microsatellite instability (MSI-H) occurs in about 15% of sporadic colorectal cancer (CRC) and is an important predictive marker for response to immune checkpoint inhibitors. To test the feasibility of a deep learning (DL)-based classi...
Middle Aged Deep Learning ROC Curve Follow-Up Studies Microsatellite Instability Feasibility Studies Adult Colorectal Neoplasms Biomarkers, Tumor Male Retrospective Studies Female Aged Aged, 80 and over Humans Prognosis
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An artificial intelligence deep learning model for identification of small bowel obstruction on plain abdominal radiographs.

The British journal of radiology Apr 27, 2021
OBJECTIVES: Small bowel obstruction is a common surgical emergency which can lead to bowel necrosis, perforation and death. Plain abdominal X-rays are frequently used as a first-line test but the availability of immediate expert radiological review i...
Feasibility Studies Sensitivity and Specificity Humans Intestinal Obstruction Male Female Intestine, Small Middle Aged Aged Radiography, Abdominal Adult Deep Learning
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The Use of a Robot to Insert an Electrode Array of Cochlear Implants in the Cochlea: A Feasibility Study and Preliminary Results.

Audiology & neuro-otology Apr 26, 2021
INTRODUCTION: Cochlear implants (CIs) are commonly used for the rehabilitation of profound bilateral hearing loss. However, patients with substantial residual acoustic hearing are potential CI candidates. Because of both improvements in technology an...
Cochlear Implantation Humans Robotics Cochlear Implants Feasibility Studies Cochlea Audiometry, Pure-Tone Electrodes, Implanted
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Hemopneumothorax detection through the process of artificial evolution - a feasibility study.

Military Medical Research Apr 25, 2021
BACKGROUND: Tension pneumothorax is one of the leading causes of preventable death on the battlefield. Current prehospital diagnosis relies on a subjective clinical impression complemented by a manual thoracic and respiratory examination. These techn...
Feasibility Studies Stethoscopes Auscultation Hemopneumothorax Artificial Intelligence Animals Swine Disease Models, Animal
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Deep Learning Improves Speed and Accuracy of Prostate Gland Segmentations on Magnetic Resonance Imaging for Targeted Biopsy.

The Journal of urology Apr 21, 2021
PURPOSE: Targeted biopsy improves prostate cancer diagnosis. Accurate prostate segmentation on magnetic resonance imaging (MRI) is critical for accurate biopsy. Manual gland segmentation is tedious and time-consuming. We sought to develop a deep lear...
Prostate Humans Feasibility Studies Software Multiparametric Magnetic Resonance Imaging Image Processing, Computer-Assisted Reproducibility of Results Image-Guided Biopsy Datasets as Topic Multimodal Imaging Prospective Studies Magnetic Resonance Imaging, Interventional Proof of Concept Study Male Prostatic Neoplasms Retrospective Studies Deep Learning Ultrasonography, Interventional Time Factors
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