The 14th Data Mining in Biomedical Informatics and Healthcare (DMBIH’26) Workshop

11/12/26-11/15/26 - Shenyang, China

The 14th Workshop on Data Mining in Biomedical Informatics and Healthcare (DMBIH) aims to bring together researchers and practitioners from data mining, artificial intelligence, biomedical informatics, and clinical research to discuss recent advances in computational methods for analyzing biomedical and healthcare data. The rapid growth of large-scale, heterogeneous datasets—including electronic health records (EHRs), biomedical images, genomics, clinical narratives, biomedical literature, and patient-generated data—creates significant opportunities as well as methodological challenges for knowledge discovery and decision support in healthcare. This workshop focuses on the development and application of advanced data mining and AI techniques, including machine learning, deep learning, large language models (LLMs), generative AI, multimodal learning, knowledge representation, and information retrieval methods for biomedical and healthcare domains. In particular, we are interested in emerging approaches that leverage foundation models and LLMs to analyze complex biomedical data such as clinical text, medical images, and multimodal patient data. This workshop focuses on the development and application of advanced data mining and AI techniques, including machine learning, deep learning, large language models (LLMs), generative AI, multimodal learning, knowledge representation, and information retrieval methods for biomedical and healthcare domains. In particular, we are interested in emerging approaches that leverage foundation models and LLMs to analyze complex biomedical data such as clinical text, medical images, and multimodal patient data.

Topics of interest include but are not limited to:

• Applications of machine learning and deep learning methods (e.g., classification, clustering, anomaly detection, topic modeling) to large-scale biomedical and electronic health record (EHR) data.
• Large language models (LLMs) and generative AI for clinical text analysis, biomedical literature mining, and clinical knowledge extraction
• Domain adaptation and fine-tuning of foundation models for biomedical and healthcare applications
• Benchmarking and evaluation of LLMs for clinical and biomedical tasks
• Foundation models and retrieval-augmented generation (RAG) for biomedical and healthcare applications
• Multimodal learning integrating clinical text, medical images, genomics, and other biomedical data modalities
• Data preprocessing, representation learning, and data quality methods to address noise, bias, and missingness in biomedical and population health datasets
• Scalable AI algorithms and distributed systems for large-scale biomedical data mining
• Federated learning and privacy-preserving AI for multi-institutional healthcare data
• Novel visualization and interactive analytics techniques for exploring complex clinical datasets
• AI and machine learning methods for time-series and longitudinal patient data analysis (e.g., patient trajectories and monitoring data)
• AI and deep learning methods for medical image analysis
• Privacy-preserving and HIPAA-compliant data mining methods for healthcare data
• AI for clinical workflow optimization and healthcare operations
• Synthetic biomedical data generation and data augmentation using generative models
• Integration of biological, clinical, and population health data for translational research
• Social media and patient-generated health data analysis for healthcare and public health
• Human-AI collaboration and human-in-the-loop learning for biomedical data mining
• Responsible, trustworthy, and explainable AI for healthcare applications

• Workshop paper submission: August 20, 2026
• Workshop paper notification of acceptance: September 18, 2026
• Camera-ready deadline and copyright forms: October 5, 2026
• Conference dates: November 12 - 15, 2026
• Workshop Date: November 14, 2026

Paper submissions will be done through the IEEE ICDM Workshop CyberChair submission system. Paper submissions should be limited to a maximum of ten (10) pages, in the IEEE 2-column format (https://www.ieee.org/conferences/publishing/templates.html) , including the bibliography and any possible appendices. Submissions longer than 10 pages will be rejected without review. All submissions will be triple-blind reviewed by the Program Committee on the basis of technical quality, relevance, originality, significance, and clarity. All accepted workshop papers will be published in formal proceedings by the IEEE Computer Society Press. One paper will be selected for the best paper award, to be awarded at the workshop.

*Online Attendance Option*: In light of potential hesitancy for international traveling, we are considering providing an online attendance option for the ICDM workshops. This would cater to those who may face travel restrictions or have concerns about in-person attendance.

• Samah Jamal Fodeh, PhD – Yale University
• Mohammad-Reza Siadat, PhD – Oakland University

To be determined.