AIMC Topic: Algorithms

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Enhancing classification of a large lower-limb motor imagery EEG dataset for BCI in knee pain patients.

Scientific data
Chronic knee osteoarthritis pain significantly impacts patients' quality of life and motor function. While motor imagery (MI)-based brain-computer interface (BCI) systems have shown promise in rehabilitation, their application to lower-limb condition...

Precise and dexterous robotic manipulation via human-in-the-loop reinforcement learning.

Science robotics
Robotic manipulation remains one of the most difficult challenges in robotics, with approaches ranging from classical model-based control to modern imitation learning. Although these methods have enabled substantial progress, they often require exten...

A dynamic examination of the digital circuit implementing the Fitzhugh-Nagumo neuron model with emphasis on low power consumption and high precision.

PloS one
Neuromorphic computing has got more attention in various tasks during recent years. The main goal of this field is to explore neural functionality in the brain. The studies of spiking neurons and Spiking Neural Networks (SNNs) are vital to understand...

Enhanced Room Temperature Sensing Properties of Tin Oxide Gas Sensors Exploiting Carbon Nanotubes: High-Accuracy Ammonia Gas Classification via Supervised Learning Regression Algorithms.

ACS sensors
The sensing properties of tin oxide (SnO) gas sensors, enhanced by the exploitation of carbon nanotubes (CNTs), were explored at room temperature. The CNT/tin oxide hybrid sensors demonstrated superior performance at room temperature compared to sing...

Construction of a feature gene and machine prediction model for inflammatory bowel disease based on multichip joint analysis.

Journal of translational medicine
BACKGROUND: Inflammatory bowel disease (IBD) is a chronic nonspecific inflammatory disorder triggered by immune responses and genetic factors. Currently, there is no cure for IBD, and its etiology remains unclear. As a result, early detection and dia...

Multi-stage framework using transformer models, feature fusion and ensemble learning for enhancing eye disease classification.

Scientific reports
Eye diseases can affect vision and well-being, so early, accurate diagnosis is crucial to prevent serious impairment. Deep learning models have shown promise for automating the diagnosis of eye diseases from images. However, current methods mostly us...

Optimized machine learning based comparative analysis of predictive models for classification of kidney tumors.

Scientific reports
The kidney is an important organ that helps clean the blood by removing waste, extra fluids, and harmful substances. It also keeps the balance of minerals in the body and helps control blood pressure. But if the kidney gets sick, like from a tumor, i...

Predicting cancer risk using machine learning on lifestyle and genetic data.

Scientific reports
Cancer remains one of the leading causes of mortality worldwide, where early detection significantly improves patient outcomes and reduces treatment burden. This study investigates the application of Machine Learning (ML) techniques to predict cancer...

Graph neural network-based drug-drug interaction prediction.

Scientific reports
With the growing variety of pharmacological compounds and the increasing need for polypharmacy, accurately predicting drug-drug interactions (DDIs) is essential to ensure both treatment efficacy and patient safety. Beneficial DDIs can enhance therape...

Integrating advanced neural network architectures with privacy enhanced encryption for secure and intelligent healthcare analytics.

Scientific reports
Healthcare data protection in our mutually connected era has emerged as an issue of serious concern with private patient information, which has been exposed more often due to data violations and cyber-attacks. Network structures CNN and LSTM as part ...