Nanomaterials play a crucial role in the biomedical field, and with the rise of the digital era, artificial intelligence (AI) has become a valuable tool in all stages of nanomaterial development, spanning from design to synthesis and characterization. In this review, we explore recent advancements in the field of AI-driven nanomaterials. Firstly, we delve into how AI can be leveraged in material design, utilizing vast databases to develop new materials. Secondly, we discuss intelligent synthesis, where AI algorithms are employed to optimize the synthesis process. Subsequently, we explore how to efficiently extract depth information from nanomaterial characterization results using AI-based methods. Lastly, we offer a glimpse into the future of biomedical nanomaterials, highlighting the potential impact of AI in this rapidly evolving field.

Despite advances in diagnostic and therapeutic technologies for cardiovascular diseases (CVDs), it remains a leading cause of mortality and morbidity worldwide. This underscores the urgency for innovative approaches aiming at early and precise detection and treatment of CVDs to reduce the disease burden. Iron oxide nanoparticles (IONPs), with their unique magnetism and bioproperties, have shown great potential in this regard. In this review, we will begin with a brief overview of the synthesis and properties of IONPs. We will then focus on the latest applications of IONPs in CVDs, including diagnosis and treatment. The use of IONPs in the integration of diagnosis and treatment for CVDs is a promising field, and will be addressed in a separate section. The translational potential and challenges of IONPs will also be discussed. In conclusion, ongoing research and development of IONP-based strategies are highly likely to address current challenges effectively, and offer more personalized and efficient options for the diagnosis and treatment of CVDs.