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Elsevier

Multimodal Data Fusion in Healthcare

AI Approaches for Precision Diagnosis

  • 1st Edition - April 21, 2026
  • Latest edition
  • Editors: Akansha Singh, Anuradha Dhull, Monika Lamba, Krishna Kant Singh
  • Language: English

Multimodal Data Fusion in Healthcare: AI Approaches for Precision Diagnosis explores the transformative potential of AI in modern medicine by integrating diverse data source… Read more

Description

Multimodal Data Fusion in Healthcare: AI Approaches for Precision Diagnosis explores the transformative potential of AI in modern medicine by integrating diverse data sources such as medical imaging, genomics, EHRs, and wearable sensors. It highlights how AI technologies are revolutionizing healthcare systems through personalized and proactive diagnostics. The book covers cutting-edge methodologies, real-world applications, and the challenges of multimodal data fusion. Topics include AI-driven diagnostics, precision medicine, real-time patient monitoring, and the integration of clinical, genomic, and wearable data, providing both theoretical foundations and practical insights. This book is essential for healthcare professionals, data scientists, and engineers, offering clear frameworks for integrating diverse data types. It addresses crucial issues like data interoperability, privacy, and technical constraints, providing practical solutions. It serves as an invaluable reference for understanding and applying AI advancements in diagnostic precision and personalized medicine.

Key features

  • Explores cutting-edge AI methodologies and their real-world applications in healthcare diagnostics
  • Provides comprehensive frameworks for integrating multimodal data, including medical imaging, genomics, EHRs, and wearable sensors
  • Addresses critical issues such as data interoperability, privacy, and technical constraints, offering practical solutions for academic and clinical settings

Readership

Healthcare professionals, data scientists, biomedical researchers, and engineers who are involved in the fields of AI, bioinformatics, and precision medicine

Table of contents

  1. Introduction to multimodal data fusion in healthcare
    Akansha Singh, Krishna Kant Singh, Anuradha Dhull, Vijendra Singh

  2. DeepSeek and multimodal AI in healthcare: enabling precision diagnosis and smart clinical decision support
    Anuradha Dhull, Akansha Singh, Saanvi Vashist, Vijendra Singh, Krishna Kant Singh

  3. From data to diagnosis: enhancing medical predictions with explainable AI
    Mitali Dogra, Ananya A., Monika Lamba

  4. Multimodal data fusion healthcare applications with Internet of Things
    Garima Sharma, Shilpa Mahajan

  5. Integration of natural language processing with electronic health records
    Shubham Bisht, Rahul Kumar, Shashank Singh, Bharti Sharma

  6. The neurological weather forecast: predicting cognitive storms before they arise
    Naween Kumar, Khushboo Devi, Shubham Sharma, Vaibhav Saini, Akansha Singh, Shreyasi Dey, Krishna Kant Singh

  7. AI–driven models for early detection and prevention of cardiovascular diseases
    Bharti Chugh, Vikrant Abbot, GunoSindhu Chakraborthy, Arpan Kumar Tripathi, Dhaneshwar Kumar Vishwakarma, Monika Lamba, Jonika Lamba

  8. Wearable sensor and clinical data fusion for cardiovascular risk prediction
    Naween Kumar, Shubham Sharma, Khushboo Devi, Ankit Dubey, Akansha Singh, Krishna Kant Singh

  9. ACUCARE—an analysis of multiple disease prediction system
    Deepti Singh, Manju, Vansh Kansal, Shreya Kataria

  10. MobileSwin‑GI: a state‑of‑the‑art hybrid deep learning model for gastrointestinal disease diagnosis
    Shaurya Jain, A. Charan Kumari, K. Srinivas

  11. Accelerating rare disease detection using generative artificial intelligence, federated learning, and multimodal data integration
    Anuradha Dhull, Akansha Singh, Kartik Pal, Krishna Kant Singh

  12. Enhancing brain tumor diagnosis using multimodal magnetic resonance imaging and computed tomography imaging with machine learning
    Nidhi Malik, Monika Lamba, Tarushi Ahlawat, Hitesh Yadav, Himanshi Vats

  13. Artificial intelligence–driven multimodal fusion for early detection of neurodegenerative diseases
    Naween Kumar, Khushboo Devi, Shubham Sharma, Ankit Dubey, Akansha Singh, Vaibhav Saini, Shreyasi Dey, Krishna Kant Singh

  14. Multimodal data fusion with machine learning and deep learning for improved attention–deficit hyperactivity disorder diagnosis
    Deepika, Shaveta Arora, Meghna Sharma

  15. A coherent review of deep learning techniques for in‑depth analysis of electroencephalogram signals
    Suvayan Chatterjee, Roohi Sille

  16. Multimodal sentiment analysis: combining bidirectional encoder representations from transformers for text and visual features
    Rajanishree M., Vishakh V. Badami, Supriya, Prakruthi Prakash Rao, M. Chaitra

  17. Social media bigotry detection
    Manju, Deepti Singh

  18. Challenges and ethics in multimodal healthcare artificial intelligence
    Akansha Singh, Krishna Kant Singh, Anuradha Dhull, Vijendra Singh

  19. Improving tumor diagnosis and prognosis through deep learning and medical imaging
    Shilpa Mahajan, Anuradha Dhull, Akansha Singh

  20. Navigating risks: a deep dive into healthcare industry analysis
    Anand Muni Mishra, Laxmi Kant Tiwari, Prabhjot Kaur, Mukund Pratap Singh

  21. Conclusion and future directions in multimodal data fusion in healthcare
    Akansha Singh, Krishna Kant Singh, Anuradha Dhull

Product details

  • Edition: 1
  • Latest edition
  • Published: April 21, 2026
  • Language: English

About the editors

AS

Akansha Singh

Prof. Akansha Singh, Professor at the School of Computer Science and Engineering, Bennett University, Greater Noida, boasts a comprehensive academic background with a B.Tech, M.Tech, and Ph.D. in Computer Science. Her doctoral studies, conducted at the prestigious IIT Roorkee, were focused on the cutting-edge fields of image processing and machine learning. A prolific author and scholar, Dr. Singh has contributed over 100 research papers and penned more than 25 books. Her editorial expertise is recognized by leading publishers such as Elsevier, Taylor and Francis, and Wiley, where she has edited books on a variety of emerging topics.Dr. Singh serves as the Associate Editor in IEEE Access, Discover Applied Science, PLOS One and guest editor in several journals. Her research interests are diverse and influential, spanning image processing, remote sensing, the Internet of Things (IoT), Blockchain and machine learning. Prof. Singh’s work in these areas not only advances the field of computer science but also significantly contributes to the broader scientific and technological community.

Affiliations and expertise
School of CSET, Bennett University, Greater Noida, India

AD

Anuradha Dhull

Dr. Anuradha Dhull has more than 13 years of teaching experience at postgraduate and undergraduate level. She is a committed researcher in the field of data science and machine learning. She completed her graduation and post-graduation with distinction. Presently four doctoral scholars are pursuing their PhD under her supervision. She specializes in DBMS, Data Structures, Big data, Operating Systems and Analysis & Design of Algorithms. She has undertaken various academic responsibilities at the department and university level. She has also guided various M.Tech and B.Tech Projects. She has more than 35 research publications in peer-reviewed journals and is also serving as a reviewer for many journals.
Affiliations and expertise
The Northcap University, India

ML

Monika Lamba

Dr. Lamba is an Assistant Professor in the Department of Computer Science and Engineering at The NorthCap University, Gurugram. She holds a B.Tech from Ansal Institute of Technology and an M.Tech from the University School of Information, Communication and Technology, both in Computer Science and Engineering. Dr. Lamba earned her Ph.D. in Machine Learning from The NorthCap University.

She has qualified for the GATE examination four times and has over seven years of experience in teaching and research. Dr. Lamba has presented papers at international conferences and published in SCI, ESCI, and Scopus-indexed journals. She has authored five book chapters, serves as a reviewer for several journals, and holds two patents. Additionally, she is a professional member of ACM and is certified in Microsoft AI-900 and AWS Cloud Practitioner.

Affiliations and expertise
The Northcap University, India

KS

Krishna Kant Singh

Dr. Krishna Kant Singh, currently the esteemed Director of Delhi Technical Campus in Greater Noida, India, is a highly experienced educator and researcher in the field of engineering and technology. He is a B.Tech and M.Tech degree, a Postgraduate Diploma in Machine Learning and Artificial Intelligence from IIIT Bangalore, a Master of Science in Machine Learning and Artificial Intelligence from Liverpool John Moores University, United Kingdom, and a Ph.D. from IIT Roorkee. Dr. Singh has made significant contributions to the academic and research community. With over 19 years of teaching experience, he has played a vital role in educating and mentoring future professionals. Dr. Singh also serves as an Associate Editor at IEEE Access, an Editorial Board Member at Applied Computing and Geosciences (Elsevier), and a Guest Editor for Complex and Intelligent Systems. His extensive publication record includes over 132 research papers. His areas of interest include Machine Learning, Deep Learning, computer vision and so on.

Affiliations and expertise
Delhi Technical Campus, Greater Noida, India

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