Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 13 1 2026 01 20 266 284 Raja Vavekanand Datalink Research and Technology Lab, Islamkot 69240, Sindh, Pakistan 2024 11 13 2025 08 17 This review explores the integration of multimodal large language models (MLLMs) with medical imaging and omics data, highlighting their transformative potential in healthcare, particularly for disease diagnosis and treatment. By combining imaging techniques like MRI, CT, and PET with omics data including genomics, transcriptomics, and proteomics. MLLMs facilitate a holistic approach to understanding disease mechanisms at molecular and structural levels. Advanced AI models, such as deep learning and machine learning algorithms, enhance diagnostic precision by identifying biomarkers, predicting survival outcomes, and enabling targeted cancer therapies. The paper examines key applications, such as multimodal AI in cancer prognosis, single-cell analysis, and radiomics in precision medicine, while discussing challenges like data complexity and feature selection. The comprehensive review underscores the impact of MLLMs on disease management, paving the way for significant improvements in clinical decision-making and patient outcomes. https://fbt.tums.ac.ir/index.php/fbt/article/view/1147 https://fbt.tums.ac.ir/index.php/fbt/article/download/1147/551