Advances in Data Science and Management - Proceedings of ICDSM 2024, Volume 1

This book includes high-quality papers presented at the Third International Conference on Data Science and Management (ICDSM 2024), organized by the Gandhi Institute for Education and Technology, Bhubaneswar, from December 13 14, 2024. It features research in which data science is used to facilitate the decision-making process in various application areas and covers a wide range of learning methods and their applications in a number of learning problems. The empirical studies, theoretical analyses and comparisons to psychological phenomena described contribute to the development of products to meet market demands. The work is presented in two volumes.

List of contents

Efficient CNN-Based Framework for Early Detection of Rice Plant Diseases.- Improved SVM based Classifier Model for Brain Tumor Early Detection in the Modern Healthcare System.- Enhanced Diabetes Prediction Among Pima Indian Women using a Hybrid Ensemble Model.- Performance Analysis of Rice Plant Disease Using DenseNet Model.- Exploiting Sentiment Analysis in Machine Learning for Mental Health Detection and Tailored Recommendations.

Product details

• Assisted by: Samarjeet Borah (Editor), Sambit Kr Mishra (Editor), Aniket Mahanti (Editor), Sambit Kr. Mishra (Editor), Zdzislaw Polkowski (Editor), Milan Tuba (Editor), Milan Tuba et al (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Release: 05.09.2025
• EAN: 9789819686384
• ISBN: 978-981-9686-38-4
• No. of pages: 416
• Illustrations: XII, 416 p. 207 illus., 188 illus. in color.
• Series: Lecture Notes in Networks and Systems
• Subjects: Natural sciences, medicine, IT, technology > Technology > General, dictionaries; Algorithmen und Datenstrukturen, Data Science, machine learning, Data Mining, Artificial Intelligence, Informationstheorie, Wissensbasierte Systeme, Expertensysteme, Information Retrieval, Data Structures and Information Theory, Data Mining and Knowledge Discovery, Data Engineering, Computational Intelligence, information extraction, Data Intensive Computing, Proceedings of ICDSM 2024