Nyhet

Applications of AI for Interdisciplinary Research

Häftad, Engelska, 2026

813 kr

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Beskrivning

Applying artificial intelligence (AI) to new fields has made AI and data science indispensable to researchers in a wide range of fields. The proliferation and successful deployment of AI algorithms are fuelling these changes, which can be seen in fields as disparate as healthcare and emerging Internet of Things (IoT) applications. Machine learning techniques, and AI more broadly, are expected to play an ever-increasing role in the modelling, simulation, and analysis of data from a wide range of fields by the interdisciplinary research community. Ideas and techniques from multidisciplinary research are being utilised to enhance AI; hence, the connection between the two fields is a two-way street at a crossroads. Algorithms for inference, sampling, and optimisation, as well as investigations into the efficacy of deep learning, frequently make use of methods and concepts from other fields of study. Cloud computing platforms may be used to develop and deploy several AI models with high computational power. The intersection between multiple fields, including math, science, and healthcare, is where the most significant theoretical and methodological problems of AI may be found. To gather, integrate, and synthesise the many results and viewpoints in the connected domains, refer to it as interdisciplinary research. In light of this, the theory, techniques, and applications of machine learning and AI, as well as how they are utilised across disciplinary boundaries, are the main areas of this research topic.This book apprises the readers about the important and cutting-edge aspects of AI applications for interdisciplinary research and guides them to apply their acquaintance in the best possible mannerThis book is formulated with the intent of uncovering the stakes and possibilities involved in using AI through efficient interdisciplinary applicationsThe main objective of this book is to provide scientific and engineering research on technologies in the fields of AI and data science and how they can be related through interdisciplinary applications and similar technologiesThis book covers various important domains, such as healthcare, the stock market, natural language processing (NLP), real estate, data security, cloud computing, edge computing, data visualisation using cloud platforms, event management systems, IoT, the telecom sector, federated learning, and network performance optimisation. Each chapter focuses on the corresponding subject outline to offer readers a thorough grasp of the concepts and technologies connected to AI and data analytics, and their emerging applications

Produktinformation

Utgivningsdatum:2026-07-19
Mått:178 x 254 x 17 mm
Vikt:580 g
Format:Häftad
Språk:Engelska
Antal sidor:296
Förlag:Taylor & Francis Ltd
ISBN:9781032740102

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Mer om författaren

Dr. Sukhpal Singh Gill (FHEA) is a Assistant Professor in Cloud Computing at School of Electronic Engineering and Computer Science (EECS), Queen Mary University of London (QMUL), UK and he is a member of Network Research Group. Prior to this, Dr. Gill has held positions as a Research Associate at Evolving Distributed Systems Lab at the School of Computing and Communications, Lancaster University, UK and also as a Postdoctoral Research Fellow at the Cloud Computing and Distributed Systems (CLOUDS) Laboratory, School of Computing and Information Systems, The University of Melbourne, Australia. He has published his PGCAP/PGCert work in highly-ranked Education Conferences and Journals. Before joining CLOUDS Lab, Dr. Gill worked in the Computer Science and Engineering Department of Thapar University, India, as a Lecturer. Dr. Gill received a Doctoral Degree specialization in Autonomic Cloud Computing from Thapar University. He worked as a Senior Research Fellow (Professional) on DST Project, Government of India. Dr. Gill was a research visitor at Monash University, University of Manitoba, University of Manchester and Imperial College London. He has recieved several awards. He has also served as the PC member for various venues. He has co-authored 150+ peer-reviewed papers and has published in prominent international journals and conferences. He serves as a Guest Editor and is a regular reviewer for multiple journals. He has also edited multiple research books He has also written for magazines such as Ars Technica, Tech Monitor, Cutter Consortium and ICT Academy. For further information, visit www.ssgill.me.

Innehållsförteckning

Part I Healthcare Chapter 1 ◾ Machine Learning-Based Prediction of Thyroid DiseaseTanjina Rhaman and Sukhpal Singh GillChapter 2 ◾ HeartGuard: A Deep Learning Approach for Cardiovascular Risk Assessment Using Biomedical Indicators Using Cloud ComputingParinaz Banifatemi and Sukhpal Singh GillChapter 3 ◾ Deep Convolutional Neural Networks-Based Skin Lesion Classification for Cancer PredictionNeelam Rathore and Sukhpal Singh GillChapter 4 ◾ Explainable AI for Cancer Prediction: A Model AnalysisAswin Kumar Govindan and Sukhpal Singh GillChapter 5 ◾ Machine Learning-Based Web Application for Breast Cancer PredictionShabnam Manjuri and Sukhpal Singh GillPart II Natural Language Programming (NLP)Chapter 6 ◾ Machine Learning-Based Opinion Mining and Visualization of News RSS Feeds for Efficient Information GainJairaj Patil and Sukhpal Singh GillPart III Economics and FinanceChapter 7 ◾ Advanced Machine Learning Models for Real Estate Price PredictionSatyam Sharma and Sukhpal Singh GillChapter 8 ◾ Stock Market Price Prediction: A Hybrid LSTM and Sequential Self-Attention-Based ApproachKaran Pardeshi, Sukhpal Singh Gill, and Ahmed M. AbdelmoniemChapter 9 ◾ Federated Learning for the Predicting Household Financial ExpenditureHo Kuen Lai, Ahmed M. Abdelmoniem, and Sukhpal Singh GillPart IV Computing and BusinessChapter 10 ◾ Deep Neural Network-Based Prediction of Breast Cancer Using Cloud ComputingSindhu Muthumanickam and Sukhpal Singh GillChapter 11 ◾ Performance Analysis of Machine Learning Models for Data Visualisation in SME: Google Cloud vs. AWS CloudJisma Choudhury and Sukhpal Singh GillPart V Security and Edge/Cloud ComputingChapter 12 ◾ Enhancing Data Security for Cloud Service Providers Using AIMuhammed Golec, Sai Siddharth Ponugoti, and Sukhpal Singh GillChapter 13 ◾ Centralised and Decentralised Fraud Detection Approaches in Federated Learning: A Performance AnalysisShai Lynch, Ahmed M. Abdelmoniem, and Sukhpal Singh GillContents ◾ viiChapter 14 ◾ AI-Based Edge Node Protection for Optimizing Security in Edge ComputingMuhammed Golec, Waleed Ul Hassan, and Sukhpal Singh GillPart VI Telecom Sector and NetworkChapter 15 ◾ Predictive Analytics for Optical Interconnection Network Performance Optimisation in Telecom SectorSuganya Senguttuvan and Sukhpal Singh GillPart VII Emotional IntelligenceChapter 16 ◾ Machine Learning-Based Emotional State Inference Using Mobile SensingDiogo Mota, Usman Naeem, and Sukhpal Singh GillPart VIII Internet of Things (IoT) and Mobile ApplicationsChapter 17 ◾ Social Event Tracking System with Real-Time Data Using Machine LearningMuhammad Usman Nazir and Sukhpal Singh Gill