AIMC Topic: Algorithms

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Fixed/prescribed-time synchronization of BAM memristive neural networks with time-varying delays via convex analysis.

Neural networks : the official journal of the International Neural Network Society
The synchronization problem of bidirectional associative memory memristive neural networks (BAMMNNs) with time-varying delays plays an essential role in the implementation and application of neural networks. Firstly, under the framework of the Filipp...

Adaptive fixed-time output synchronization for complex dynamical networks with multi-weights.

Neural networks : the official journal of the International Neural Network Society
This paper addresses fixed-time output synchronization problems for two types of complex dynamical networks with multi-weights (CDNMWs) by using two types of adaptive control methods. Firstly, complex dynamical networks with multiple state and output...

Utility of artificial intelligence to identify antihyperglycemic agents poisoning in the USA: introducing a practical web application using National Poison Data System (NPDS).

Environmental science and pollution research international
Clinical effects of antihyperglycemic agents poisoning may overlap each other. So, distinguishing exposure to these pharmaceutical drugs may take work. This study examined the application of machine learning techniques in identifying antihyperglycemi...

Wayfinding artificial intelligence to detect clinically meaningful spots of retinal diseases: Artificial intelligence to help retina specialists in real world practice.

PloS one
AIM/BACKGROUND: To aim of this study is to develop an artificial intelligence (AI) that aids in the thought process by providing retinal clinicians with clinically meaningful or abnormal findings rather than just a final diagnosis, i.e., a "wayfindin...

Diagnosis of liver diseases based on artificial intelligence.

Biotechnology & genetic engineering reviews
Due to a series of problems in the diagnosis of liver disease, the mortality rate of liver disease patients is very high. Therefore, it is necessary for doctors and researchers to find a more effective non-invasive diagnostic method to meet clinical ...

A primer on artificial intelligence in pancreatic imaging.

Diagnostic and interventional imaging
Artificial Intelligence (AI) is set to transform medical imaging by leveraging the vast data contained in medical images. Deep learning and radiomics are the two main AI methods currently being applied within radiology. Deep learning uses a layered s...

Super High-Throughput Screening of Enzyme Variants by Spectral Graph Convolutional Neural Networks.

Journal of chemical theory and computation
Finding new enzyme variants with the desired substrate scope requires screening through a large number of potential variants. In a typical enzyme engineering workflow, it is possible to scan a few thousands of variants, and gather several candidates...

New Frontiers in Oncological Imaging With Computed Tomography: From Morphology to Function.

Seminars in ultrasound, CT, and MR
The latest evolutions in Computed Tomography (CT) technology have several applications in oncological imaging. The innovations in hardware and software allow for the optimization of the oncological protocol. Low-kV acquisitions are possible thanks to...

Artificial intelligence in molecular de novo design: Integration with experiment.

Current opinion in structural biology
In this mini review, we capture the latest progress of applying artificial intelligence (AI) techniques based on deep learning architectures to molecular de novo design with a focus on integration with experimental validation. We will cover the progr...

Spatial gradient consistency for unsupervised learning of hyperspectral demosaicking: application to surgical imaging.

International journal of computer assisted radiology and surgery
PURPOSE: Hyperspectral imaging has the potential to improve intraoperative decision making if tissue characterisation is performed in real-time and with high-resolution. Hyperspectral snapshot mosaic sensors offer a promising approach due to their fa...