AIMC Topic: Algorithms

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Deep Learning-Based Algorithm for the Detection and Characterization of MRI Safety of Cardiac Implantable Electronic Devices on Chest Radiographs.

Korean journal of radiology
OBJECTIVE: With the recent development of various MRI-conditional cardiac implantable electronic devices (CIEDs), the accurate identification and characterization of CIEDs have become critical when performing MRI in patients with CIEDs. We aimed to d...

Deep Learning Algorithm for Simultaneous Noise Reduction and Edge Sharpening in Low-Dose CT Images: A Pilot Study Using Lumbar Spine CT.

Korean journal of radiology
OBJECTIVE: The purpose of this study was to assess whether a deep learning (DL) algorithm could enable simultaneous noise reduction and edge sharpening in low-dose lumbar spine CT.

No Fine-Tuning, No Cry: Robust SVD for Compressing Deep Networks.

Sensors (Basel, Switzerland)
A common technique for compressing a neural network is to compute the -rank ℓ2 approximation Ak of the matrix A∈Rn×d via SVD that corresponds to a fully connected layer (or embedding layer). Here, is the number of input neurons in the layer, is the...

Evaluating the Work Productivity of Assembling Reinforcement through the Objects Detected by Deep Learning.

Sensors (Basel, Switzerland)
With the rapid development of deep learning, computer vision has assisted in solving a variety of problems in engineering construction. However, very few computer vision-based approaches have been proposed on work productivity's evaluation. Therefore...

On the Optimization of Regression-Based Spectral Reconstruction.

Sensors (Basel, Switzerland)
Spectral reconstruction (SR) algorithms attempt to recover hyperspectral information from RGB camera responses. Recently, the most common metric for evaluating the performance of SR algorithms is the Mean Relative Absolute Error (MRAE)-an ℓ1 relative...

ARMA-Based Segmentation of Human Limb Motion Sequences.

Sensors (Basel, Switzerland)
With the development of human motion capture (MoCap) equipment and motion analysis technologies, MoCap systems have been widely applied in many fields, including biomedicine, computer vision, virtual reality, etc. With the rapid increase in MoCap dat...

iBitter-Fuse: A Novel Sequence-Based Bitter Peptide Predictor by Fusing Multi-View Features.

International journal of molecular sciences
Accurate identification of bitter peptides is of great importance for better understanding their biochemical and biophysical properties. To date, machine learning-based methods have become effective approaches for providing a good avenue for identify...

A machine learning approach for the factorization of psychometric data with application to the Delis Kaplan Executive Function System.

Scientific reports
While a replicability crisis has shaken psychological sciences, the replicability of multivariate approaches for psychometric data factorization has received little attention. In particular, Exploratory Factor Analysis (EFA) is frequently promoted as...

A siamese network with adaptive gated feature fusion for individual knee OA features grades prediction.

Scientific reports
Grading individual knee osteoarthritis (OA) features is a fine-grained knee OA severity assessment. Existing methods ignore following problems: (1) more accurately located knee joints benefit subsequent grades prediction; (2) they do not consider kne...

An approach to rapidly assess sepsis through multi-biomarker host response using machine learning algorithm.

Scientific reports
Sepsis is a life-threatening condition and understanding the disease pathophysiology through the use of host immune response biomarkers is critical for patient stratification. Lack of accurate sepsis endotyping impedes clinicians from making timely d...