Multimodal Data Fusion in Healthcare

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. 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. 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.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.

• Introduction to multimodal data fusion in healthcareDeepSeek and multimodal AI in healthcare: enabling precision diagnosis and smart clinical decision supportFrom data to diagnosis: enhancing medical predictions with explainable AIMultimodal data fusion healthcare applications with Internet of ThingsIntegration of natural language processing with electronic health recordsThe neurological weather forecast: predicting cognitive storms before they ariseAI–driven models for early detection and prevention of cardiovascular diseasesWearable sensor and clinical data fusion for cardiovascular risk predictionACUCARE—an analysis of multiple disease prediction systemMobileSwin‑GI: a state‑of‑the‑art hybrid deep learning model for gastrointestinal disease diagnosisAccelerating rare disease detection using generative artificial intelligence, federated learning, and multimodal data integrationEnhancing brain tumor diagnosis using multimodal magnetic resonance imaging and computed tomography imaging with machine learningArtificial intelligence–driven multimodal fusion for early detection of neurodegenerative diseasesMultimodal data fusion with machine learning and deep learning for improved attention–deficit hyperactivity disorder diagnosisA coherent review of deep learning techniques for in‑depth analysis of electroencephalogram signalsMultimodal sentiment analysis: combining bidirectional encoder representations from transformers for text and visual featuresSocial media bigotry detectionChallenges and ethics in multimodal healthcare artificial intelligenceImproving tumor diagnosis and prognosis through deep learning and medical imagingNavigating risks: a deep dive into healthcare industry analysisConclusion and future directions in multimodal data fusion in healthcare