Advances in Multimodal Large Language Models for Healthcare

Nyhet

Methods and Applications

Inbunden, Engelska, 2026

AvHari Mohan Pandey,Marcello Trovati,Hamid Bouchachia,Dilip Prasad,Arun Prakash Agrawal

2 329 kr

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Advances in Multimodal Large Language Models for Healthcare: Methods and Applications provides valuable insights on Large Language Models in healthcare applications for researchers, academics, and practitioners. The book explains key concepts, including artificial intelligence, machine learning, deep learning, and the evolution of neural networks and transformer models. It then covers generative AI and LLMs for a wide spectrum of healthcare applications, including mental health, clinical decision support, interactive system design, and sensitive analysis. Readers will find this to be a valuable deep dive into the emergent intersection of LLMs and health care, with guidance into applications, technical and programming methods, and more.

Although LLMs have shown some promising results in the healthcare sector, numerous challenges need to be addressed before they can be used in patient care. The two key issues with the adoption of LLMs regarding healthcare settings are reliability, transparency, interpretation of results and bias (data and algorithm) management. Unless properly and adequately validated, there may be incorrect medical information provided by the LLM-based systems, which can lead to misdiagnosis or hazardous treatment errors. At this point, LLMs have not only been used for decision making or documentation, they have also proven to be useful in patient engagement through QA systems, medical chatbots, and virtual healthcare.

Covers the basics of Artificial Intelligence, Machine Learning, and Deep Learning
Highlights the evolution of Transformer Based Deep Neural Network Models
Presents key concepts and methods in Generative AI and Large Language Models (LLMs)
Discusses the application of LLMs in clinical decision-making
Delves into the utility of LLMs for virtual assistance and human-machine interaction
Describes transformer-based pretrained models for healthcare applications

Produktinformation

Utgivningsdatum2026-09-01
Mått191 x 235 x undefined mm
Vikt450 g
FormatInbunden
SpråkEngelska
Antal sidor250
FörlagElsevier Science
ISBN9780443438882

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Hari Mohan Pandey is a professor of data science and artificial intelligence at the School of Technology at Bournemouth University, UK. I am featured in the 2021, 2022, 2023, and 2024 World Ranking list of Top 2% scientists by Sandford University. I am specialized in Computer Science & Engineering. My research area includes artificial intelligence, soft computing techniques, natural language processing, language acquisition, machine learning, deep learning, and computer vision. I am the author of various books in computer science engineering (algorithms, programming, and evolutionary algorithms). Recently, my book entitled “State of the Art on Grammatical Inference Using Evolutionary Method " has been published in Elsevier. I have published over 150 scientific papers in reputed journals and conferences. I am serving on the editorial board of reputed journals (including Neural Networks Elsevier, Applied Soft Computing Elsevier, Swarm and Evolutionary Computing Elsevier, Neural Computing and Applications Springer, IEEE Transactions of Evolutionary Computation, IEEE Transactions on Industrial Informatics, Neurocomputing Springer, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Neural Networks and Learning Systems and Knowledge-Based Systems Elsevier) as action editor, associate editor, and guest editor. I am the reviewer of top international conferences such as GECCO, CEC, IJCNN, BMVC, AAAI, etc. I have delivered expert talks as a keynote and invited speaker. I am a fellow of the HEA of the UK Professional Standards Framework (UKPSF) and have a rich teaching experience at the higher education level. I have delivered lecturers in international summer/winter schools. I have been given the prestigious award “The Global Award for the Best Computer Science Faculty of the Year 2015, the award for completing the INDO-US project “GENTLE, award (Certificate of Exceptionalism) from the Prime Minister of India, and the award for developing innovative teaching and learning models for higher education. In the past, I worked as a Sr. Lecturer in the Computer Science department at Edge Hill University. I also worked as a research fellow in machine learning at the School of Technology at Middlesex University London where I worked on a European Commission project- DREAM4CARS.Marcello Trovati is a Professor in Computer Science in the Department of Computer Science, Edge Hill University, as well as the Editor in Chief of Applied Artificial Intelligence, Taylor & Francis. After having obtained his PhD in Mathematics at the University of Exeter in 2007, specialising in theoretical dynamical systems with singularities, he accepted a position as algorithm tester and research specialist at a medium sized software development company. His main responsibility was to create test and documents state-of-the-art statistical algorithms to analyse big datasets. He then moved to the newly created Dublin IBM Research Lab to carry out research mainly in the field of knowledge discovery, text mining, and mathematical modelling, where he gained valuable business and research experience through collaboration with several scientists both at IBM, and at academic institutions. He was involved in a number of research projects in collaboration with other IBM Research Centres and academic institutionsHe then joined Coventry University to take up a position as Teaching Fellow, and subsequently the University of Derby as a lecturer, during which he was involved various multi-disciplinary projects focussing on mathematical modelling, algorithm design, and big data analytics. In 2016 Marcello joined the Computer Science Department at Edge Hill University as a senior lecturer and he was recently awarded a Readership in Computer Science. He is involved in several research themes and projects. He is co-leading the STEM Data Research centre and is actively involved in the Productivity and Innovation Lab, aiming to collaborate and support SMEs in Lancashire.Hamid Bouchachia is a Professor of Data Science and Intelligent Systems at the Department of Computing and Informatics, Faculty of Science and Technology at Bournemouth University, UK. His research encompasses various topics of Artificial Intelligence and Data Science. Specifically, he is interested in scalable machine learning, scalable online, active, semi-supervised learning for data streams, scalable pattern recognition including deep learning and hierarchical (graphical) models, reasoning, decision making, big data technologies and high-performance computing for ML. He published more than 180 papers in journals and conferences and edited several special issues and volumes. He currently serves as program committee member for many conferences and acts as Editor for 4 journals: IEEE Transactions on AI, Journal of Big Data (Springer), Evolving Systems (Springer) and Network: Computation in Neural Systems (Taylor & Francis). He is member of Evolving Intelligent Systems (EIS) Technical Committee (TC) of the IEEE Systems, Man and Cybernetics Society and member of the IEEE Taskforce for Adaptive and Evolving Fuzzy Systems of the IEEE Computational Intelligence Society. He led and coordinated EU projects and proposals and in various areas, particularly around machine learning and data science and their applications in various domains such as security, cybersecurity, disaster management, ubiquitous health, smart environments, industrial monitoring; smart energy; and assistive technologies. In particular, he coordinated the PROTEUS project (scalable online machine learning for predictive analytics) and participated as principal investigator in a number of collaborative projects, e.g., BRIDGE, INFER, EXTREMEXP, ARTEMIS, and PRESERVE.Dilip K. Prasad is a professor at Department of Computer Science, UiT The Arctic University of Norway. He received the Ph.D and B.Tech degree in Computer Science and Engineering from Nanyang Technological University, Singapore and Indian Institute of Technology (Indian School of Mines), Dhanbad, India in 2013 and 2003 respectively. He was a senior research fellow at Nanyang Technological University, Singapore from 2015-2019 and research Fellow at National University of Singapore from 2012-2015. Prior to Ph. D, he has worked for 5 years with IBM, Infosys, Mediatek and Philips. He has been selected as fellow for Kauffman Global Scholarship in 2011, in which he was trained in entrepreneurship at Harvard University, MIT, Stanford University and Kauffman Foundation. He is a co-author of book titled "Interpretability in Deep Learning", Springer, 2023. He has secured research and innovation grant from EU, RCN as a PI/co-PI of about ~20 million Euro. He has published 100+ internationally peer-reviewed research articles and patents. His research interests include image processing, pattern recognition and artificial intelligence. He was the founder of Techaloo (successful exit 2018) and gpl4you.com and advisor for prepdoor.com , niflr.com.Arun Prakash Agrawal is currently working as a Professor with School of Computer Science Engineering and Technology, Bennett University Greater Noida, India. He obtained his PhD and master’s in computer science and engineering from Guru Gobind Singh Indraprastha University, New Delhi. He was the gold medallist of his batch. Prior to his current assignment he has served many academic institutions including Sharda University Greater Noida and Amity University, Noida. He has several research papers to his credit in refereed journals and conferences of international repute in India and abroad. He has also taught short term courses at the Swinburne University of Technology, Melbourne, Australia and Amity Global Business School, Singapore. His research interests include Machine Learning, Software Testing, Artificial Intelligence, Soft Computing, and Nature Inspired Optimization. He has a wide experience of organizing international conferences technically co-sponsored by IEEE and Springer. He has also organized several international faculty development programs and workshops for capacity building. During his tenure as Sharda University Greater Noida, he led a team of 50+ young and dynamic faculty members. He also has a good exposure of outcome-based education and several national and international rankings and accreditations.

1. The New Era of Artificial Intelligence2. Introduction to Machine Learning and Data Science3. Deep Learning Models and Application in Healthcare4. Evolution of Transformer Based Deep Learning Models5. Marching from AI to Generative AI6. Introduction to Large Language Models7. Applications of Large Language Models8. Generative AI and LLMs for Healthcare9. LLMs as a Decision Support System in Healthcare Settings10. LLMs as an Interaction and Virtual Assistance Systems for Healthcare11. LLMs for Handling Mental Disorders and Sensitivity Analysis12. Challenges with Generative AI and LLMs in Healthcare Settings