In Biomedical materials (Bristol, England)
Nanomedicine has recently experienced unprecedented growth and development. However, the complexity of operations at the nanoscale introduces a layer of difficulty in the clinical translation of nanodrugs and biomedical nanotechnology. This problem is further exacerbated when engineering and optimizing nanomaterials for biomedical purposes. To navigate this issue, artificial intelligence algorithms have been applied for data analysis and inference, allowing for a more applicable understanding of the complex interaction amongst the abundant variables in a system involving the synthesis or use of nanomedicine. Here, we report on the current relationship and implications of nanomedicine and artificial intelligence. Particularly, we explore artificial intelligence as a tool for enabling nanomedicine in the context of nanodrug screening and development, brain machine interfaces and nanotoxicology. We also report on the current state and future direction of nanomedicine and artificial intelligence in cancer, diabetes, and neurological disorder therapy.
Hayat Hasaan, Nukala Arijit, Nyamira Anthony, Fan Jinda, Wang Ping
Artificial Intelligence, Deep Learning, Machine Learning, Nanomedicine, Nanotechnology, Theranostic, Type 1 Diabetes