Workshop Overview
The 1st International Workshop on Large Language Models for Healthcare and Radiotherapy (LLM4HR) at IEEE BIBM 2026 is dedicated to addressing the rapidly growing intersection of artificial intelligence and healthcare & radiation oncology. The increasing complexity of clinical data — ranging from electronic health records and patient-reported outcomes to medical imaging and treatment planning datasets — presents both significant challenges and transformative opportunities.
Recognizing the critical need for robust, intelligent systems to manage noise, missing data, high-dimensional information, and multi-modalities, this workshop aims to bridge the gap between cutting-edge methodological development and safe, effective clinical implementation. Its primary purpose is to convene researchers, clinicians, and AI practitioners to explore how machine learning, deep learning, data science, LLMs, multimodal AI, and agentic AI can revolutionize key aspects of healthcare and radiation oncology — including data preprocessing, outcome prediction, treatment planning, workflow optimization, and quality assurance.
By focusing on practical solutions such as clinical note summarization, 3D dose prediction, anomaly detection, novel visualization techniques, and response-guided treatment planning and optimization, this workshop seeks to foster interdisciplinary collaboration, accelerate translational research, and ultimately improve cancer patient care through intelligent, automated, and context-aware radiation therapy systems.
The workshop is held in conjunction with the IEEE International Conference on Bioinformatics and Biomedicine 2026 (BIBM 2026). Accepted papers will be included in the corresponding proceedings.
