LLMs4MI 2024

Call for Papers

In recent years, the rapid advancements in Large Language Models (LLMs), like GPT-4, Claude 3, Gemini, and others, have demonstrated their immense capabilities in understanding and generating natural language and showcased their immense potential across various domains. In the Medical Informatics (MI) community, there is significant interest in leveraging LLMs in a variety of tasks ranging from general tasks such as improving patient assessment, therapeutics, diagnostics and treatment, specialized tasks such as primary care, surgery and oncology to clinical support tasks such as medical assistants and clinical research tasks relating to trials, compliance and data management.

This workshop focuses on the diverse applications of advanced LLMs in MI, addressing the unique challenges, methodologies, and impacts on healthcare practices. We welcome the submission of original papers on all topics related to LLMs in medical informatics, with particular interest in but not limited to:

Clinical Decision Support Systems: Utilizing LLMs to aid diagnosis, treatment planning, and personalized medicine.

Information Extraction from Medical Reports: Workflows and the use of LLMS to extract relevant information for diagnosis and treatment of diseases.

Medical Literature Analysis: Applying LLMs for summarizing, querying, and interpreting vast amounts of medical texts and research papers.

Predictive Analytics: Leveraging LLMs for forecasting disease outbreaks, patient outcomes, and resource allocation in healthcare settings.

Healthcare Education, Medical Training and Simulation: Using LLMs to create realistic training scenarios for medical education and procedural training.

Ethical and Legal Implications of LLMs in Healthcare: Addressing concerns related to bias, privacy, and regulatory compliance.

Medical data lifecycle: Using LLMs to enhance many aspects of the data lifecycle including the collection and analysis of clinical trials data and improving data quality in medical databases and registries.

Committees

Steering Committee

Stefan Decker, RWTH Aachen University, Aachen, Germany
Oya Beyan, University of Cologne, Cologne, Germany
Sonja Schimmler, Fraunhofer FOKUS, Berlin, Germany

Organizers

Sulayman Sowe, RWTH Aachen University, Aachen, Germany
Zeyd Boukhers, Fraunhofer FIT, Sankt Augustin, Germany
Yongli Mou, RWTH Aachen University, Aachen, Germany
Alexander Neumann, RWTH Aachen University, Aachen, Germany

Publicity Chair

Nagaraj Bahubali Asundi, Fraunhofer FIT, Sankt Augustin, Germany

Program Committee (alphabetized by first name)

Admantios Kumpis, University of Cologne, Cologne, Germany
Carolin Schneider, University Hospital Aachen, Aachen, Germany
Diego Collarana Vargas, Fraunhofer FIT, Sankt Augustin, Germany
Feng Zhou, Renmin University of China, Beijing, China
Huizi Yu, Amazon Science, Virginia, USA
Hussam Ghanem, ICB, UMR 6306, CNRS, Université de Bourgogne, 21000 Dijon, France
Kerstin Denecke, Bern University of Applied Sciences, Bern, Switzerland
Lizhou Fan, Harvard Medical School, MA, USA
Lingxiao Kong, Fraunhofer FIT, Sankt Augustin, Germany
Rohit Kumar, Head R&D, CSC eGov, MietY, Government of India; Research Scholar, IIT Delhi, School of AI; Limited Partner 500 Startups, Inc, India
Sandra Geisler, RWTH Aachen University, Aachen, Germany
Yu Wang, Shanghai Jiao Tong University, Shanghai, P. R. China

Keynote

Priv.-Doz. Dr. med. Dipl.-Phys. Daniel Truhn, MD, M.Sc.

Short Biography
Daniel is a physicist, imaging scientist, and clinical radiologist with a dedicated focus on machine learning and magnetic resonance imaging. After studying physics at RWTH Aachen University and Imperial College in London, he studied medicine at RWTH Aachen University. In 2013, he completed his MD thesis on the compatibility of positron emission tomography and magnetic resonance imaging and joined the Department of Diagnostic and Interventional Radiology (University Hospital Aachen) to become a board-certified clinical radiologist in 2019. Besides his clinical work, he pursued his research interests in machine learning as a fellow at the Institute of Imaging and Computer Vision (RWTH Aachen University) for two years before returning to the clinic where he currently leads the interdisciplinary research group “AI in Medical Imaging”. His research focuses on bringing machine learning-methods into clinical practice and on bridging the gaps between research possibilities and clinical applicability. His recent publications are listed on Google Scholar and PubMed

Submission

Author Submission Guidelines

Papers have to be submitted via the workshop's EasyChair submission page.

Submitted papers (.pdf format) must use the A4 IEEE Manuscript Templates for Conference Proceedings.

Submitted papers may be 6 to 8 pages. Up to two additional pages may be added for references. The reference pages must only contain references. Overlength papers will be rejected without review. Please ensure that you submit your papers with the full and final list of authors in the correct order. The author list registered for each submission is not allowed to be changed in any way after the paper submission deadline. Please remember to add Keywords to your submission.

Please proofread your submission carefully. It is essential that the language use in the paper is clear and correct so that it is easily understandable. (Either US English or UK English spelling conventions are acceptable.)

All the papers will go through the double-blind peer review process. Authors’ names and affiliations should not appear in the submitted paper. Authors’ prior work should be cited in the third person. Authors should also avoid revealing their identities and/or institutions in the text, figures, links, etc.

Papers submitted to LLMs4MI must be the original work of the authors. The may not be simultaneously under review elsewhere. Publications that have been peer-reviewed and have appeared at other conferences or workshops may not be submitted to LLMs4MI. Authors should be aware that IEEE has a strict policy with regard to plagiarism.

All accepted papers in LLMs4MI 2024 and FLLM 2024 will be submitted to IEEEXplore for possible publication.

Important Dates

Submission		August 15, 2024
Notification of acceptance		October 05, 2024
Registration		Please visit the FLLM 2024 registration page
Camera-Ready submission		October 20, 2024
Workshop at FLLM 2024		TBD

All submission deadlines are end-of-day in the Anywhere on Earth (AoE) time zone.

The First International Workshop
on Large Language Models Applications in Medical Informatics
(LLMs4MI2024)

In conjunction with the
The Second International Conference on Foundation and Large Language Models (FLLM2024)
Dubai, UAE