AIMC Topic: Algorithms

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Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI With Limited Training Data.

IEEE transactions on medical imaging
In this work we reduce undersampling artefacts in two-dimensional (2D) golden-angle radial cine cardiac MRI by applying a modified version of the U-net. The network is trained on 2D spatio-temporal slices which are previously extracted from the image...

Automated sleep scoring: A review of the latest approaches.

Sleep medicine reviews
Clinical sleep scoring involves a tedious visual review of overnight polysomnograms by a human expert, according to official standards. It could appear then a suitable task for modern artificial intelligence algorithms. Indeed, machine learning algor...

A Heuristic Approach to Overcome Architectural Barriers Using a Robotic Wheelchair.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The Mobility Enhancement roBotic (MEBot) wheelchair was developed to improve the safety and accessibility of wheelchair users when facing architectural barriers. MEBot uses pneumatic actuators attached to its frame and six wheels to provide curb asce...

Clustering Neural Patterns in Kernel Reinforcement Learning Assists Fast Brain Control in Brain-Machine Interfaces.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Neuroprosthesis enables the brain control on the external devices purely using neural activity for paralyzed people. Supervised learning decoders recalibrate or re-fit the discrepancy between the desired target and decoder's output, where the correct...

Machine learning for tissue diagnostics in oncology: brave new world.

British journal of cancer
Machine learning is an exciting technology with broad application in big data analysis, as well as increasingly in specialised healthcare. As a diagnostic tool in tissue workup and pathology, it has the potential for personalised and stratified appro...

Machine learning-based prediction of breast cancer growth rate in vivo.

British journal of cancer
BACKGROUND: Determining the rate of breast cancer (BC) growth in vivo, which can predict prognosis, has remained elusive despite its relevance for treatment, screening recommendations and medicolegal practice. We developed a model that predicts the r...

Distance-based protein folding powered by deep learning.

Proceedings of the National Academy of Sciences of the United States of America
Direct coupling analysis (DCA) for protein folding has made very good progress, but it is not effective for proteins that lack many sequence homologs, even coupled with time-consuming conformation sampling with fragments. We show that we can accurate...

Developmental validation of PACE™: Automated artifact identification and contributor estimation for use with GlobalFiler™ and PowerPlex® fusion 6c generated data.

Forensic science international. Genetics
DNA mixture interpretation remains one of the major challenges in forensic DNA analysis. DNA mixture samples are inherently complex due to several factors including the variations in the quantity of DNA, the presence of non-allelic artifactual peaks ...

Combining a gravitational search algorithm, particle swarm optimization, and fuzzy rules to improve the classification performance of a feed-forward neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: A feed-forward neural network (FNN) is a type of artificial neural network that has been widely used in medical diagnosis, data mining, stock market analysis, and other fields. Many studies have used FNN to develop medical d...

Digital whole-slide image analysis for automated diatom test in forensic cases of drowning using a convolutional neural network algorithm.

Forensic science international
Diatom examinations have been widely used to perform drowning diagnosis in forensic practice. However, current methods for recognizing diatoms, which use light or electron microscopy, are time-consuming and laborious and often result in false positiv...