Emerging Trends in Artificial Intelligence and Machine Learning

This volume comprises selected peer-reviewed proceedings of the 12th International Conference on Signal Processing and Integrated Networks (SPIN 2025). It aims to provide a comprehensive and broad-spectrum picture of state-of-the-art research and development in signal processing, IoT sensors, systems and technologies, cloud computing, wireless communication, and wireless sensor networks. This volume will provide a valuable resource for those in academia and industry.

Section 1: Foundations of AI and Machine Learning. - Analyzing the Performance of Classification Models and Sampling Techniques on Imbalanced Datasets. - TextPrep: Automating the Process of Text Data Pre-Processing by Leveraging Self-Supervised Learning. - Advancing Transfer Learning with GAP, Depth Constraints, and Average Depth Constraints for Diverse Datasets. - Knparaphraser: A Kannada Paraphrasing Model Based on Novel Data Augmentation Framework. - Section 2: AI for Health and Biomedical Research. - Accelerating DNA Sequence Alignment Using Optimized AI Techniques. - Drug Discovery for Mycobacterium Tuberculosis: A Synergistic Approach using QSAR and Machine Learning. - Analysis of Parkinson s Disease Detection using Machine Learning Algorithms. - Designing a Malaria Detection Scheme Using Convolutional Neural Network (CNN) and TensorFlow-Based Deep Learning Model. - A Machine Learning Approach for Anomaly Detection in COVID-19 PCR Test Results Using Isolation Forests. - Optimizing ICU Patient Management through Predictive Analysis. - Exploring Deep Learning Approaches for Sleep Apnea Detection. - etc.