AIMC Topic: Algorithms

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A Smartphone-Based Detection System for Tomato Leaf Disease Using EfficientNetV2B2 and Its Explainability with Artificial Intelligence (AI).

Sensors (Basel, Switzerland)
The occurrence of tomato diseases has substantially reduced agricultural output and financial losses. The timely detection of diseases is crucial to effectively manage and mitigate the impact of episodes. Early illness detection can improve output, r...

An advanced approach for the electrical responses of discrete fractional-order biophysical neural network models and their dynamical responses.

Scientific reports
The multiple activities of neurons frequently generate several spiking-bursting variations observed within the neurological mechanism. We show that a discrete fractional-order activated nerve cell framework incorporating a Caputo-type fractional diff...

Machine learning: a powerful tool for identifying key microbial agents associated with specific cancer types.

PeerJ
Machine learning (ML) includes a broad class of computer programs that improve with experience and shows unique strengths in performing tasks such as clustering, classification and regression. Over the past decade, microbial communities have been imp...

Deep fit_predic: a novel integrated pyramid dilation EfficientNet-B3 scheme for fitness prediction system.

Computer methods in biomechanics and biomedical engineering
This study introduces novel deep learning (DL) techniques for effective fitness prediction using a person's health data. Initially, pre-processing is performed in which data cleaning, one-hot encoding and data normalization are performed. The pre-pro...

Artificial intelligence and its clinical application in Anesthesiology: a systematic review.

Journal of clinical monitoring and computing
PURPOSE: Application of artificial intelligence (AI) in medicine is quickly expanding. Despite the amount of evidence and promising results, a thorough overview of the current state of AI in clinical practice of anesthesiology is needed. Therefore, o...

Machine learning in medication prescription: A systematic review.

International journal of medical informatics
BACKGROUND: Medication prescription is a complex process that could benefit from current research and development in machine learning through decision support systems. Particularly pediatricians are forced to prescribe medications "off-label" as chil...

Ensemble of local and global information for Protein-Ligand Binding Affinity Prediction.

Computational biology and chemistry
Accurately predicting protein-ligand binding affinities is crucial for determining molecular properties and understanding their physical effects. Neural networks and transformers are the predominant methods for sequence modeling, and both have been s...

Integrating artificial intelligence, machine learning, and deep learning approaches into remediation of contaminated sites: A review.

Chemosphere
The growing number of contaminated sites across the world pose a considerable threat to the environment and human health. Remediating such sites is a cumbersome process with the complexity originating from the need for extensive sampling and testing ...

A Review of Machine Learning and Algorithmic Methods for Protein Phosphorylation Site Prediction.

Genomics, proteomics & bioinformatics
Post-translational modifications (PTMs) have key roles in extending the functional diversity of proteins and, as a result, regulating diverse cellular processes in prokaryotic and eukaryotic organisms. Phosphorylation modification is a vital PTM that...

Theoretical modeling and machine learning-based data processing workflows in comprehensive two-dimensional gas chromatography-A review.

Journal of chromatography. A
In recent years, comprehensive two-dimensional gas chromatography (GC × GC) has been gradually gaining prominence as a preferred method for the analysis of complex samples due to its higher peak capacity and resolution power compared to conventional ...