Practical Applications of Machine Learning and AI: Medicine, Environmental Science, Transportation, and Education

Practical Applications of Machine Learning and AI: Medicine, Environmental Science, Transportation, and Education

Toufik Mzili (Chouaib Doukkali University, Morocco) and Adarsh Kumar Arya (Harcourt Butler Technical University, India)
Release Date: February, 2025|Copyright: © 2025 |Pages: 448
DOI: 10.4018/979-8-3373-1399-3
ISBN13: 9798337313993|ISBN13 Softcover: 9798337314006|EISBN13: 9798337314013
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Description & Coverage
Description:

Optimization, machine learning, and artificial intelligence are revolutionizing society, medicine, environmental science, transportation, and education. In medicine, AI-driven diagnostics and personalized treatments improve patient outcomes, while optimization streamlines resource allocation. Environmental science benefits from machine learning's ability to analyze complex datasets, enabling sustainable practices and climate predictions. In transportation, optimization enhances logistics and traffic flow, with AI powering autonomous vehicles and predictive maintenance. Across all areas, these technologies drive efficiency, innovation, and smarter decision-making.

Practical Applications of Machine Learning and AI: Medicine, Environmental Science, Transportation, and Education provides deeper understanding of the complexities of optimization, machine learning and AI, examining their theoretical foundations. Furthermore, it contributes to the ongoing advancement of these fields, practical applications, and transformative potentials. Covering topics including Medical Image Segmentation, student performance prediction, and pothole detection, this book is an excellent resource for computer scientists, researchers, scholars, academicians, professionals, and more.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Anomaly Detection
  • Artificial Intelligence (AI)
  • ChatGPT
  • Civic Education
  • Deforestation
  • Forest Monitoring
  • Hydrogen Energy
  • Machine Learning
  • Medical Image Segmentation
  • Neurodegenerative Disease Diagnosis and Classification
  • Pothole Detection
  • Python
  • Student Performance Prediction
  • Traffic Management
  • U-Net Architecture
  • VigilEye
  • Wastewater Treatment
  • YOLO Models
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Editor/Author Biographies
Mzili Toufik holds the position of Assistant Professor in the Department of Computer Science at the Faculty of Science, Chouaib Doukkali University. Recognized as a distinguished researcher, he has made noteworthy contributions to the fields of metaheuristics, optimization, and scheduling problems. His scholarly impact is evident through numerous publications in esteemed Q1 journals. Additionally, Dr. Mzili Toufik has demonstrated his expertise as a peer reviewer for several prestigious journals, showcasing his commitment to advancing the academic discourse in his field.
Adarsh Arya competent professional with nearly 20 years of experience in Research and Development / Teaching chemical engineering graduates and post graduates. • Exercises judgment within generally defined practices in selecting methods & techniques for obtaining teaching solutions; ensuring compliance to quality measures and maintenance requisite documentation as well as records • Skills in managing the administrative activities entailing student management, faculty appraisal/training and upholding of the institution's motto • Proficiency in teaching Oil and Gas Pipeline and core chemical engineering subjects to Chemical Engineering Graduate and post graduate students. • Experience in developing curriculum to accommodate different learning styles & maximize students' comprehension • Received research awards • Exposure in working with T.A.N.A.P. Gas Pipeline Project at Worley Parsons. • Exposure in planning and organizing day-to-day research activities and resolving the procedural problem as appropriate to the timely accomplishment of research objectives • An effective leader with proven skills in leading teams during the project phase, training & guiding team members and enabling knowledge sharing among the team
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