Information System Design: Intelligent Healthcare Informatics
Description
This book presents a collection of high-quality, peer-reviewed research papers from 9th International Conference on Information System Design and Intelligent Applications (ISDIA 2025), held in Dubai, UAE, from January 3-4, 2025. It covers a wide range of topics in computer science and information technology, including data mining and data warehousing, high-performance computing, parallel and distributed computing, computational intelligence, soft computing, big data, cloud computing, grid computing, cognitive computing, and information security.
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Vikrant Bhateja is an associate professor in Department of Electronics Engineering Faculty of Engineering and Technology (UNSIET), Veer Bahadur Singh Purvanchal University, Jaunpur, Uttar Pradesh, India. He holds a doctorate in biomedical imaging (ECE) with a total academic teaching experience of 20 years with around 190 publications in reputed international conferences, journals, and online book chapter contributions; out of which 39 papers are published in SCIE indexed high impact factored journals. One of his papers published in Review of Scientific Instruments (RSI) Journal (under American International Publishers) has been selected as "Editor Choice Paper of the Issue'' in 2016. Among the international conference publications, four papers have received "Best Paper Award." He has delivered nearly 22 keynotes, invited talks in international conferences, ATAL, TEQIP, and other AICTE sponsored FDPs and STTPs.
Farhad Oroumchian is a professor of Artificial Intelligence, Natural Language Processing, and Machine Learning in University of Wollongong (Dubai Campus). He has 24 years of experience teaching AI, machine learning, and databases. Dr Oroumchian has served at various capacities in the university ranging from Acting Chair of College to Associate Dean of Education. He is currently the head of AI and Intelligent Systems Research Cluster. Prior to joining university, his previous posts include the chair of the Department of Software Engineering at the University of Tehran and manager of IT Services in the Faculty of Engineering of the University of Tehran. Prof Oroumchian has worked as a senior research engineer at TextWise LLC in Syracuse, New York, from 1996 till 1999. Prior to 1996, he has worked as a project manager and consultant for various companies in USA.
Jinshan Tang is a professor of Health Informatics in the Department of Health Administration and Policy. Before joining George Mason University, Dr. Tang was a full professor in the College of Computing at Michigan Technological University and a founding director of the Joint Center for Biocomputing and Digital Health. Dr. Tang's research covers broad areas related to image processing and artificial intelligence. His specific research interests include biomedical image analysis, biomedical imaging, artificial intelligence in medicine (e.g., computer-aided cancer detection, AI for COVID-19 detection). He has obtained over three million dollars grants as a PI or Co-PI and has published more than 110+ refereed journal and conference papers. He has also served as a committee member at various international conferences. He is a senior member of IEEE and a co-chair of the Technical Committee on Information Assurance and Intelligent Multimedia-Mobile Communications, IEEE SMC society.
Zaid Omar (senior member, IEEE) received the master's degree in data communications from the University of Sheffield and the Ph.D. degree in electrical engineering from the Imperial College London, in 2012. He is currently an associate professor with Universiti Teknologi Malaysia. His research interests include computer vision, medical imaging, and image fusion. Dr. Omar was crowned the best science communicator for FameLab Malaysia 2017-one of the biggest science communication competitions in the world organized by British Council.
Content
Enhancing Early Glaucoma Diagnosis through Machine Learning Techniques.- Classification of Blood Disorders using Machine Learning Algorithms.- Leveraging AI for Early and Precise Detection of Thyroid Disorder.- Enhancing Stroke Prediction through Machine Learning: A Comparative Study of Key Algorithms.- Comparative Analysis of Machine Learning Techniques in Diabetes Prediction.- Exploring Emotion Recognition through EEG Brainwave Data: A Comparative Analysis of Machine Learning and Deep Learning Approaches.- "Optical Flow-Based Localization of Anatomical Landmarks in Colonoscopy".- Efficient Respiratory Disease Classification Using Customized CNN on a Large Kaggle Dataset.- Comparative Analysis of Regressor Models for Predicting Heart Attack Risk: A Comprehensive Evaluation Using Regression Metrics and Visualization.- Comparative Analysis of Data Balancing Techniques in Prostate Cancer Classification Using Machine Learning and Deep Learning.- AI as the Stepping Stone of Revolution in Maxillofacial Prosthodontic Shade Selection.- GradTX Net: Leveraging Transformers for Accurate Diabetic Foot Ulcer Severity Grading.- Deep Learning-Based Skin Cancer Classification and Localization: A Comprehensive Approach for Accurate Diagnosis and Localization of Skin Cancers.- Predicting Breast Cancer Recurrence Using Machine Learning and Deep Learning Models: A Comparative Study.