AIMC Topic: Neural Networks, Computer

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TCDformer: A transformer framework for non-stationary time series forecasting based on trend and change-point detection.

Neural networks : the official journal of the International Neural Network Society
Although time series prediction models based on Transformer architecture have achieved significant advances, concerns have arisen regarding their performance with non-stationary real-world data. Traditional methods often use stabilization techniques ...

Mode combinability: Exploring convex combinations of permutation aligned models.

Neural networks : the official journal of the International Neural Network Society
We explore element-wise convex combinations of two permutation-aligned neural network parameter vectors Θ and Θ of size d. We conduct extensive experiments by examining various distributions of such model combinations parametrized by elements of the ...

Clinical utilization of artificial intelligence in predicting therapeutic efficacy in pulmonary tuberculosis.

Journal of infection and public health
Traditional methods for monitoring pulmonary tuberculosis (PTB) treatment efficacy lack sensitivity, prompting the exploration of artificial intelligence (AI) to enhance monitoring. This review investigates the application of AI in monitoring anti-tu...

Synthetic biological neural networks: From current implementations to future perspectives.

Bio Systems
Artificial neural networks, inspired by the biological networks of the human brain, have become game-changing computing models in modern computer science. Inspired by their wide scope of applications, synthetic biology strives to create their biologi...

An Innovative Inducer of Platelet Production, Isochlorogenic Acid A, Is Uncovered through the Application of Deep Neural Networks.

Biomolecules
(1) Background: Radiation-induced thrombocytopenia (RIT) often occurs in cancer patients undergoing radiation therapy, which can result in morbidity and even death. However, a notable deficiency exists in the availability of specific drugs designed f...

Person identification with arrhythmic ECG signals using deep convolution neural network.

Scientific reports
Over the past decade, the use of biometrics in security systems and other applications has grown in popularity. ECG signals in particular are attracting increased attention due to their characteristics, which are required for a trustworthy identifica...

Virtual histological staining of unlabeled autopsy tissue.

Nature communications
Traditional histochemical staining of post-mortem samples often confronts inferior staining quality due to autolysis caused by delayed fixation of cadaver tissue, and such chemical staining procedures covering large tissue areas demand substantial la...

A deep learning dataset for sample preparation artefacts detection in multispectral high-content microscopy.

Scientific data
High-content image-based screening is widely used in Drug Discovery and Systems Biology. However, sample preparation artefacts may significantly deteriorate the quality of image-based screening assays. While detection and circumvention of such artefa...

Modelling the GDP of KSA using linear and non-linear NNAR and hybrid stochastic time series models.

PloS one
BACKGROUND: Gross domestic product (GDP) serves as a crucial economic indicator for measuring a country's economic growth, exhibiting both linear and non-linear trends. This study aims to analyze and propose an efficient and accurate time series appr...

Deep learning for automatic bowel-obstruction identification on abdominal CT.

European radiology
RATIONALE AND OBJECTIVES: Automated evaluation of abdominal computed tomography (CT) scans should help radiologists manage their massive workloads, thereby leading to earlier diagnoses and better patient outcomes. Our objective was to develop a machi...