AIMC Topic: Neural Networks, Computer

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mCNN-glucose: Identifying families of glucose transporters using a deep convolutional neural network based on multiple-scanning windows.

International journal of biological macromolecules
Glucose transporters are essential carrier proteins that function on the phospholipid bilayer to facilitate glucose diffusion across cell membranes. The transporters play many physiological and pathological roles in addition to absorption and metabol...

Integrating artificial intelligence with endoscopic ultrasound in the early detection of bilio-pancreatic lesions: Current advances and future prospects.

Best practice & research. Clinical gastroenterology
The integration of Artificial Intelligence (AI) in endoscopic ultrasound (EUS) represents a transformative advancement in the early detection and management of biliopancreatic lesions. This review highlights the current state of AI-enhanced EUS (AI-E...

Neural Architecture Search for biomedical image classification: A comparative study across data modalities.

Artificial intelligence in medicine
Deep neural networks have significantly advanced medical image classification across various modalities and tasks. However, manually designing these networks is often time-consuming and suboptimal. Neural Architecture Search (NAS) automates this proc...

Machine Learning-Based Quantification of Lateral Flow Assay Using Smartphone-Captured Images.

Biosensors
Lateral flow assay has been extensively used for at-home testing and point-of-care diagnostics in rural areas. Despite its advantages as convenient and low-cost testing, it suffers from poor quantification capacity where only yes/no or positive/negat...

Sentiment analysis of tweets employing convolutional neural network optimized by enhanced gorilla troops optimization algorithm.

Scientific reports
Sentiment analysis has become a difficult and important task in the current world. Because of several features of data, including abbreviations, length of tweet, and spelling error, there should be some other non-conventional methods to achieve the a...

Forecasting cardiovascular disease mortality using artificial neural networks in Sindh, Pakistan.

BMC public health
Cardiovascular disease (CVD) is a leading cause of death and disability worldwide, and its incidence and prevalence are increasing in many countries. Modeling of CVD plays a crucial role in understanding the trend of CVD death cases, evaluating the e...

Improving groundwater quality predictions in semi-arid regions using ensemble learning models.

Environmental science and pollution research international
Groundwater resources constitute one of the primary sources of freshwater in semi-arid and arid climates. Monitoring the groundwater quality is an essential component of environmental management. In this study, a comprehensive comparison was conducte...

A discriminative multi-modal adaptation neural network model for video action recognition.

Neural networks : the official journal of the International Neural Network Society
Research on video-based understanding and learning has attracted widespread interest and has been adopted in various real applications, such as e-healthcare, action recognition, affective computing, to name a few. Amongst them, video-based action rec...

Synergistic learning with multi-task DeepONet for efficient PDE problem solving.

Neural networks : the official journal of the International Neural Network Society
Multi-task learning (MTL) is an inductive transfer mechanism designed to leverage useful information from multiple tasks to improve generalization performance compared to single-task learning. It has been extensively explored in traditional machine l...

Multi-view clustering based on feature selection and semi-non-negative anchor graph factorization.

Neural networks : the official journal of the International Neural Network Society
Multi-view clustering has garnered significant attention due to its capacity to utilize information from multiple perspectives. The concept of anchor graph-based techniques was introduced to manage large-scale data better. However, current methods re...