AIMC Topic: Feasibility Studies

Clear Filters Showing 421 to 430 of 950 articles

Feature Selection and Validation of a Machine Learning-Based Lower Limb Risk Assessment Tool: A Feasibility Study.

Sensors (Basel, Switzerland)
Early and self-identification of locomotive degradation facilitates us with awareness and motivation to prevent further deterioration. We propose the usage of nine squat and four one-leg standing exercise features as input parameters to Machine Learn...

Feasibility of robot-assisted neuroendovascular procedures.

Journal of neurosurgery
OBJECTIVE: Geographic factors prevent equitable access to urgent advanced neuroendovascular treatments. Robotic technologies may enable remote endovascular procedures in the future. The authors performed a translational, benchtop-to-clinical study to...

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
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
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
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
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
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...

Predicting postoperative pain following root canal treatment by using artificial neural network evaluation.

Scientific reports
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
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...