AIMC Topic: Algorithms

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LDMRes-Net: A Lightweight Neural Network for Efficient Medical Image Segmentation on IoT and Edge Devices.

IEEE journal of biomedical and health informatics
In this study, we propose LDMRes-Net, a lightweight dual-multiscale residual block-based convolutional neural network tailored for medical image segmentation on IoT and edge platforms. Conventional U-Net-based models face challenges in meeting the sp...

Artificial Intelligence Application in Skull Bone Fracture with Segmentation Approach.

Journal of imaging informatics in medicine
This study aims to evaluate an AI model designed to automatically classify skull fractures and visualize segmentation on emergent CT scans. The model's goal is to boost diagnostic accuracy, alleviate radiologists' workload, and hasten diagnosis, ther...

Generalisation capabilities of machine-learning algorithms for the detection of the subthalamic nucleus in micro-electrode recordings.

International journal of computer assisted radiology and surgery
PURPOSE: Micro-electrode recordings (MERs) are a key intra-operative modality used during deep brain stimulation (DBS) electrode implantation, which allow for a trained neurophysiologist to infer the anatomy in which the electrode is placed. As DBS t...

Directly training temporal Spiking Neural Network with sparse surrogate gradient.

Neural networks : the official journal of the International Neural Network Society
Brain-inspired Spiking Neural Networks (SNNs) have attracted much attention due to their event-based computing and energy-efficient features. However, the spiking all-or-none nature has prevented direct training of SNNs for various applications. The ...

Mittag-Leffler stability and application of delayed fractional-order competitive neural networks.

Neural networks : the official journal of the International Neural Network Society
In the article, the Mittag-Leffler stability and application of delayed fractional-order competitive neural networks (FOCNNs) are developed. By virtue of the operator pair, the conditions of the coexistence of equilibrium points (EPs) are discussed a...

Progressive Neighbor-masked Contrastive Learning for Fusion-style Deep Multi-view Clustering.

Neural networks : the official journal of the International Neural Network Society
Fusion-style Deep Multi-view Clustering (FDMC) can efficiently integrate comprehensive feature information from latent embeddings of multiple views and has drawn much attention recently. However, existing FDMC methods suffer from the interference of ...

Unsupervised and semi-supervised domain adaptation networks considering both global knowledge and prototype-based local class information for Motor Imagery Classification.

Neural networks : the official journal of the International Neural Network Society
The non-stationarity of EEG signals results in variability across sessions, impeding model building and data sharing. In this paper, we propose a domain adaptation method called GPL, which simultaneously considers global knowledge and prototype-based...

Predicting efficacy of antiseizure medication treatment with machine learning algorithms in North Indian population.

Epilepsy research
PURPOSE: This study aimed to develop a classifier using supervised machine learning to effectively assess the impact of clinical, demographical, and biochemical factors in accurately predicting the antiseizure medications (ASMs) treatment response in...

Investigating the influence of streetscape environmental characteristics on pedestrian crashes at intersections using street view images and explainable machine learning.

Accident; analysis and prevention
Examining the relationship between streetscape features and road traffic accidents is pivotal for enhancing roadway safety. While previous studies have primarily focused on the influence of street design characteristics, sociodemographic features, an...

Algorithmic bias: Social science research integration through the 3-D Dependable AI Framework.

Current opinion in psychology
Algorithmic bias has emerged as a critical challenge in the age of responsible production of artificial intelligence (AI). This paper reviews recent research on algorithmic bias and proposes increased engagement of psychological and social science re...