AIMC Topic: Reproducibility of Results

Clear Filters Showing 1791 to 1800 of 5908 articles

A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram.

Nature communications
This study compares a deep learning interpretation of 23 echocardiographic parameters-including cardiac volumes, ejection fraction, and Doppler measurements-with three repeated measurements by core lab sonographers. The primary outcome metric, the in...

Automated volume measurement of abdominal adipose tissue from entire abdominal cavity in Dixon MR images using deep learning.

Radiological physics and technology
The purpose of this study was to realize an automated volume measurement of abdominal adipose tissue from the entire abdominal cavity in Dixon magnetic resonance (MR) images using deep learning. Our algorithm involves a combination of extraction of t...

Overtriage, Undertriage, and Value of Care after Major Surgery: An Automated, Explainable Deep Learning-Enabled Classification System.

Journal of the American College of Surgeons
BACKGROUND: In single-institution studies, overtriaging low-risk postoperative patients to ICUs has been associated with a low value of care; undertriaging high-risk postoperative patients to general wards has been associated with increased mortality...

Motion grading of high-resolution quantitative computed tomography supported by deep convolutional neural networks.

Bone
Image quality degradation due to subject motion confounds the precision and reproducibility of measurements of bone density, morphology and mechanical properties from high-resolution peripheral quantitative computed tomography (HR-pQCT). Time-consumi...

Temporomandibular joint segmentation in MRI images using deep learning.

Journal of dentistry
OBJECTIVES: Temporomandibular joint (TMJ) internal derangements (ID) represent the most prevalent temporomandibular joint disorder (TMD) in the population and its diagnosis typically relies on magnetic resonance imaging (MRI). TMJ articular discs in ...

Machine-Learning Classification of Pulse Waveform Quality.

Sensors (Basel, Switzerland)
Pulse measurements made using wearable devices can aid the monitoring of human physiological condition. Accurate estimation of waveforms is often difficult for nonexperts; motion artifacts may occur during tonometry measurements when the skin-sensor ...

Effect of AI-assisted software on inter- and intra-observer variability for the X-ray bone age assessment of preschool children.

BMC pediatrics
BACKGROUND: With the rapid development of deep learning algorithms and the rapid improvement of computer hardware in the past few years, AI-assisted diagnosis software for bone age has achieved good diagnostic performance. The purpose of this study w...

Fuzzy inference system (FIS) - long short-term memory (LSTM) network for electromyography (EMG) signal analysis.

Biomedical physics & engineering express
A wide range of application domains,s such as remote robotic control, rehabilitation, and remote surgery, require capturing neuromuscular activities. The reliability of the application is highly dependent on an ability to decode intentions accurately...

MODENN: A Shallow Broad Neural Network Model Based on Multi-Order Descartes Expansion.

IEEE transactions on pattern analysis and machine intelligence
Deep neural networks have achieved great success in almost every field of artificial intelligence. However, several weaknesses keep bothering researchers due to its hierarchical structure, particularly when large-scale parallelism, faster learning, b...

Mobile robot path planning with reformative bat algorithm.

PloS one
Mobile robot path planning has attracted much attention as a key technology in robotics research. In this paper, a reformative bat algorithm (RBA) for mobile robot path planning is proposed, which is employed as the control mechanism of robots. The D...