The Autism Spectrum Disorder (ASD) diagnosis and detection in its initial stages is a more complex issue in the face of the wide-ranging, diverse nature and causes. Subsequent literature inclined towards a possible correlation of gut microbiome with ASD, and its disclosure presents a more promising attribute for imminent discovery conduits. The dataset on gut microbiome associated with ASD focuses specifically on the microbial compositions obtained through 16S rRNA sequencing. This study presents a novel method that integrates Artificial Intelligence employing various Machine Learning (ML) robust classifiers such that Support Vector Machines (SVM), Random Forest, k-Nearest Neighbors (KNN), L... More >

Air pollution has emerged as a critical challenge, directly affecting human health, urban sustainability, and climate systems. Traditional air-quality index (AQI) prediction models often struggle to provide timely alerts because they are not very sensitive to changes over time and are hard to understand. This paper proposes a Neuro-Inspired Alert System for Air Quality Prediction (NAS--AQP) that incorporates an ensemble learning approach using voting regression to enhance input quality, followed by classification through a Spiking Neural Network (SNN). The system is designed such that it captures the temporal and nonlinear relationships between air pollutants such as Nitrogen Dioxide ($NO_2$... More >