AIMC Topic: Algorithms

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Dual-Mode Fluorescent/Intelligent Lateral Flow Immunoassay Based on Machine Learning Algorithm for Ultrasensitive Analysis of Chloroacetamide Herbicides.

Analytical chemistry
Given the harmful effect of pesticide residues, it is essential to develop portable and accurate biosensors for the analysis of pesticides in agricultural products. In this paper, we demonstrated a dual-mode fluorescent/intelligent (DM-f/DM-i) latera...

Morphological classification of neurons based on Sugeno fuzzy integration and multi-classifier fusion.

Scientific reports
In order to extract more important morphological features of neuron images and achieve accurate classification of the neuron type, a method is proposed that uses Sugeno fuzzy integral integration of three optimized deep learning models, namely AlexNe...

Bee-inspired insights: Unleashing the potential of artificial bee colony optimized hybrid neural networks for enhanced groundwater level time series prediction.

Environmental monitoring and assessment
Analysis of the change in groundwater used as a drinking and irrigation water source is of critical importance in terms of monitoring aquifers, planning water resources, energy production, combating climate change, and agricultural production. Theref...

Cell recognition based on features extracted by AFM and parameter optimization classifiers.

Analytical methods : advancing methods and applications
Intelligent technology can assist in the diagnosis and treatment of disease, which would pave the way towards precision medicine in the coming decade. As a key focus of medical research, the diagnosis and prognosis of cancer play an important role in...

Machine Learning Approach in Dosage Individualization of Isoniazid for Tuberculosis.

Clinical pharmacokinetics
INTRODUCTION: Isoniazid is a first-line antituberculosis agent with high variability, which would profit from individualized dosing. Concentrations of isoniazid at 2 h (C), as an indicator of safety and efficacy, are important for optimizing therapy.

Physics-informed machine learning algorithms for forecasting sediment yield: an analysis of physical consistency, sensitivity, and interpretability.

Environmental science and pollution research international
The sediment transport, involving the movement of the bedload and suspended sediment in the basins, is a critical environmental concern that worsens water scarcity and leads to degradation of land and its ecosystems. Machine learning (ML) algorithms ...

Computationally intelligent real-time security surveillance system in the education sector using deep learning.

PloS one
Real-time security surveillance and identity matching using face detection and recognition are central research areas within computer vision. The classical facial detection techniques include Haar-like, MTCNN, AdaBoost, and others. These techniques e...

Research on short-term power load forecasting based on VMD and GRU.

PloS one
The traditional method for power load forecasting is susceptible to various factors, including holidays, seasonal variations, weather conditions, and more. These factors make it challenging to ensure the accuracy of forecasting results. Additionally,...

Multi-Modal Electrophysiological Source Imaging With Attention Neural Networks Based on Deep Fusion of EEG and MEG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The process of reconstructing underlying cortical and subcortical electrical activities from Electroencephalography (EEG) or Magnetoencephalography (MEG) recordings is called Electrophysiological Source Imaging (ESI). Given the complementarity betwee...

A Least-Square Unified Framework for Spatial Filtering in SSVEP-Based BCIs.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The steady-state visual evoked potential (SSVEP) has become one of the most prominent BCI paradigms with high information transfer rate, and has been widely applied in rehabilitation and assistive applications. This paper proposes a least-square (LS)...