Emerging Trends in Artificial Intelligence and Machine Learning

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.

• Erscheinungsdatum: 14.11.2025
• Autor/Autorin: J. K. Rai
• Reihe: Springer Nature Proceedings excluding Computer Science
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 30.5 MB
• Verlag: SPRINGER
• Sprache: Englisch
• Umfang: 515 Seiten
• ISBN: 9789819699711
• Lieferung: Sofort per Download
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• Kompatibilität: Lesbar auf Geräten und Apps mit PDF-Unterstützung.