AIMC Topic: Algorithms

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PET scatter estimation using deep learning U-Net architecture.

Physics in medicine and biology
Positron emission tomography (PET) image reconstruction needs to be corrected for scatter in order to produce quantitatively accurate images. Scatter correction is traditionally achieved by incorporating an estimated scatter sinogram into the forward...

Optimization Algorithm of Moving Object Detection Using Multiscale Pyramid Convolutional Neural Networks.

Computational intelligence and neuroscience
Object detection and recognition is a very important topic with significant research value. This research develops an optimised model of moving target identification based on CNN to address the issues of insufficient positioning information and low t...

Preciseness of artificial intelligence for lateral cephalometric measurements.

Journal of orofacial orthopedics = Fortschritte der Kieferorthopadie : Organ/official journal Deutsche Gesellschaft fur Kieferorthopadie
BACKGROUND: The aim of the study was to assess the accuracy and efficiency of a new artificial intelligence (AI) method in performing lateral cephalometric radiographic measurements.

A Scoping Review of Artificial Intelligence Research in Rhinology.

American journal of rhinology & allergy
BACKGROUND: A considerable volume of possible applications of artificial intelligence (AI) in the field of rhinology exists, and research in the area is rapidly evolving.

QuantumTox: Utilizing quantum chemistry with ensemble learning for molecular toxicity prediction.

Computers in biology and medicine
Molecular toxicity prediction plays an important role in drug discovery, which is directly related to human health and drug fate. Accurately determining the toxicity of molecules can help weed out low-quality molecules in the early stage of drug disc...

External Validation of an Artificial Intelligence Device for Intracranial Hemorrhage Detection.

World neurosurgery
BACKGROUND: Artificial intelligence applications have gained traction in the field of cerebrovascular disease by assisting in the triage, classification, and prognostication of both ischemic and hemorrhagic stroke. The Caire ICH system aims to be the...

Are Deep Learning Structural Models Sufficiently Accurate for Virtual Screening? Application of Docking Algorithms to AlphaFold2 Predicted Structures.

Journal of chemical information and modeling
Machine learning-based protein structure prediction algorithms, such as RosettaFold and AlphaFold2, have greatly impacted the structural biology field, arousing a fair amount of discussion around their potential role in drug discovery. While there ar...

A study of autoencoders as a feature extraction technique for spike sorting.

PloS one
Spike sorting is the process of grouping spikes of distinct neurons into their respective clusters. Most frequently, this grouping is performed by relying on the similarity of features extracted from spike shapes. In spite of recent developments, cur...

Bounded synchronization for uncertain master-slave neural networks: An adaptive impulsive control approach.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the bounded synchronization of the discrete-time master-slave neural networks (MSNNs) with uncertainty. To deal with the unknown parameter in the MSNNs, a parameter adaptive law combined with the impulsive mechanism is propose...

A Federated Learning-Inspired Evolutionary Algorithm: Application to Glucose Prediction.

Sensors (Basel, Switzerland)
In this paper, we propose an innovative Federated Learning-inspired evolutionary framework. Its main novelty is that this is the first time that an Evolutionary Algorithm is employed on its own to directly perform Federated Learning activity. A furth...