AIMC Topic: Feasibility Studies
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Performance of a 3D convolutional neural network in the detection of hypoperfusion at CT pulmonary angiography in patients with chronic pulmonary embolism: a feasibility study.
European radiology experimental
Sep 24, 2021
BACKGROUND: Chronic pulmonary embolism (CPE) is a life-threatening disease easily misdiagnosed on computed tomography. We investigated a three-dimensional convolutional neural network (CNN) algorithm for detecting hypoperfusion in CPE from computed t...
Incorporating metadata in HIV transmission network reconstruction: A machine learning feasibility assessment.
PLoS computational biology
Sep 22, 2021
HIV molecular epidemiology estimates the transmission patterns from clustering genetically similar viruses. The process involves connecting genetically similar genotyped viral sequences in the network implying epidemiological transmissions. This tech...
Feasibility assessment of infectious keratitis depicted on slit-lamp and smartphone photographs using deep learning.
International journal of medical informatics
Sep 17, 2021
BACKGROUND: This study aims to investigate how infectious keratitis depicted on slit-lamp and smartphone photographs can be reliably assessed using deep learning.
Feasibility of late gadolinium enhancement (LGE) in ischemic cardiomyopathy using 2D-multisegment LGE combined with artificial intelligence reconstruction deep learning noise reduction algorithm.
International journal of cardiology
Sep 10, 2021
BACKGROUND: Despite the low spatial resolution of 2D-multisegment late gadolinium enhancement (2D-MSLGE) sequences, it may be useful in uncooperative patients instead of standard 2D single segmented inversion recovery gradient echo late gadolinium en...
Selection, Visualization, and Interpretation of Deep Features in Lung Adenocarcinoma and Squamous Cell Carcinoma.
The American journal of pathology
Sep 8, 2021
Although deep learning networks applied to digital images have shown impressive results for many pathology-related tasks, their black-box approach and limitation in terms of interpretability are significant obstacles for their widespread clinical uti...
Carcinoma, Squamous Cell
Reproducibility of Results
Sensitivity and Specificity
Male
Humans
Neural Networks, Computer
Female
Feasibility Studies
Image Interpretation, Computer-Assisted
Deep Learning
Datasets as Topic
Adenocarcinoma of Lung
Image Processing, Computer-Assisted
Lung Neoplasms
Diagnosis, Differential
Predicting postoperative pain following root canal treatment by using artificial neural network evaluation.
Scientific reports
Aug 26, 2021
This study aimed to evaluate the accuracy of back propagation (BP) artificial neural network model for predicting postoperative pain following root canal treatment (RCT). The BP neural network model was developed using MATLAB 7.0 neural network toolb...
Evaluation of the feasibility of explainable computer-aided detection of cardiomegaly on chest radiographs using deep learning.
Scientific reports
Aug 19, 2021
We examined the feasibility of explainable computer-aided detection of cardiomegaly in routine clinical practice using segmentation-based methods. Overall, 793 retrospectively acquired posterior-anterior (PA) chest X-ray images (CXRs) of 793 patients...
Large Vessel Occlusion Prediction in the Emergency Department with National Institutes of Health Stroke Scale Components: A Machine Learning Approach.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Aug 15, 2021
OBJECTIVE: To determine the feasibility of using a machine learning algorithm to screen for large vessel occlusions (LVO) in the Emergency Department (ED).
Shape-Sensing Robotic-Assisted Bronchoscopy in the Diagnosis of Pulmonary Parenchymal Lesions.
Chest
Aug 9, 2021
BACKGROUND: The landscape of guided bronchoscopy for the sampling of pulmonary parenchymal lesions is evolving rapidly. Shape-sensing robotic-assisted bronchoscopy (ssRAB) recently was introduced as means to allow successful sampling of traditionally...
Patterns of Metastatic Disease in Patients with Cancer Derived from Natural Language Processing of Structured CT Radiology Reports over a 10-year Period.
Radiology
Aug 3, 2021
Background Patterns of metastasis in cancer are increasingly relevant to prognostication and treatment planning but have historically been documented by means of autopsy series. Purpose To show the feasibility of using natural language processing (NL...
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