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MediKS @ CIKM 2025

Workshop on Advances in Medical Knowledge Systems: LLMs, RAG and Foundation Models

More information to come: stay tuned!

Find the important dates

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Find the call for papers

here⁠

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Find the schedule

here⁠

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Overview

In recent years, AI has shown remarkable potential in transforming healthcare by enabling systems that can interpret, retrieve, and reason over vast amounts of medical knowledge.

Yet, building effective and trustworthy medical knowledge systems remains a complex challenge. These systems must not only integrate diverse data modalities and evolving clinical evidence but also support safe, explainable, and context-aware decision-making in real-world settings.

This workshop aims to explore emerging solutions at the intersection of large language models, retrieval-augmented generation, and foundation or agentic models. By bringing together researchers, clinicians, and developers, the workshop will foster interdisciplinary collaboration to tackle key issues such as personalization, clinical reasoning, safety, and deployment.

By fostering discussions and collaborations among researchers and practitioners, this workshop seeks to shape the next generation of evidence-driven, knowledge-centric AI solutions for medicine.

Important Dates

Submission deadline: August 31, 2025

Acceptance Notification: September 30, 2025

Workshop day: November 14, 2025

Camera-ready versions of accepted papers due: TBD

Accepted papers will be published in CEUR-WS proceedings. Authors may opt out of publication if preferred.

Deadlines refer to 23:59 (11:59pm) in the AoE (Anywhere on Earth) time zone.

Topics

The workshop centers on the development of medical knowledge systems grounded in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and foundation or agentic models, with the aim of enabling safe, interpretable, and evidence-based AI in healthcare.

In particular, we welcome contributions on the following topics:

Knowledge Grounding for Medical LLMs: Methods for aligning LLMs with structured biomedical databases (e.g., UMLS, SNOMED CT), clinical notes, or guideline repositories.

Biomedical Retrieval-Augmented Generation (RAG): Techniques for indexing, retrieving, and generating responses grounded in reliable medical literature or patient-specific data.

Foundation and Agentic Models in Clinical Practice: Explorations of how generalist models can be adapted to support diagnosis, treatment planning, triage, and other critical care tasks.

Multimodal Reasoning Systems: Approaches that combine text, imaging, EHRs, and temporal signals for comprehensive clinical understanding and decision-making.

Factuality and Interpretability: Tools and techniques for controlling hallucinations, increasing trust, and surfacing explanations in high-stakes environments.

Bias and Fairness in Medical AI: Methods for detecting, quantifying, and mitigating bias in model outputs, particularly across demographic and clinical subgroups.

Patient-Centered Personalization: Systems that provide tailored care recommendations and model individual patient trajectories using recommender techniques and adaptive modeling.

Evaluation, Benchmarks, and Deployment Case Studies: Novel evaluation metrics, real-world use cases, lessons from clinical implementation, and open-source tools or datasets.

Other Emerging Topics: As this is a rapidly evolving area, we encourage submissions that propose new directions, conceptual frameworks, or community resources for knowledge-centric medical AI.

Call for papers

We are pleased to invite you to contribute to the First Workshop on Advances in Medical Knowledge Systems @ CIKM 2025, the premier venue for research on the foundations and applications of recommendation technologies in medical field. Each accepted paper is expected to be presented in person. Accepted papers will likely be published in CEUR-WS proceedings, but authors may opt out of publication if preferred.

We encourage a broad spectrum of contributions, from theoretical studies advancing the foundations of medical knowledge systems, to applied research and industry papers that tackle real-world challenges in clinical deployment, integration, and evaluation.

Reviewing Process

All submissions will be peer-reviewed (double-blind) by the program committee and judged by their relevance to the workshop, especially to the main themes identified above, and their potential to generate discussion. Submissions not properly anonymized will be desk-rejected without review.

Submission Guidelines

Authors are invited to submit original, full-length research papers that are not previously published, accepted to be published, or being considered for publication in any other forum. Full-length papers should satisfy the standard requirements of top-tier international research conferences.

Manuscripts should be submitted to

Easychair⁠

site in PDF format, using the 2-column ACM sigconf template, see https://www.acm.org/publications/proceedings-template.

We invite research contributions, position, demo and opinion papers. Submissions may take the form of:

Full papers (up to 8 pages, including appendices, references not included), presenting mature research results.

Short papers (up to 4 pages, including appendices, references not included), presenting ongoing work, demos, position, or opinion papers.

Extended abstracts (2–4 pages, references not included), describing early-stage ideas, preliminary experiments, or promising research directions.

Papers that include text generated from a large-scale language model (LLM), such as ChatGPT, are prohibited unless this produced text is presented as a part of the paper’s experimental analysis. AI tools may be used to edit and polish authors’ work, such as using LLMs for light editing of their text (e.g., automate grammar checks, word autocorrect, and other editing of author-written text), but text “produced entirely” by generative/AI models is not allowed.

At least one author of each accepted paper must register to present the work on-site in Seoul, Korea as scheduled in the conference program.

We encourage but do not require authors to release any code and/or datasets associated with their paper.

All submissions and reviews will be handled electronically. Papers must be submitted via

EasyChair⁠

https://easychair.org/my/conference?conf=mediks2025⁠

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