A concise review: the synergy between artificial intelligence and biomedical nanomaterials that empowers nanomedicine. (5th August 2021)

• Record Type: Journal Article
• Authors: Hayat, Hasaan; Nukala, Arijit; Nyamira, Anthony; Fan, Jinda; Wang, Ping
• Is Part Of: Biomedical materials. Volume 16:Number 5(2021)
• Publication Date: 2021-08-05
• Subjects: nanomedicine -- nanotechnology -- machine learning -- deep learning -- artificial intelligence -- type 1 diabetes -- cancer; Biomedical materials -- Periodicals; 610.28
• DOI: 10.1088/1748-605X/ac15b2
• Languages: English
• ISSNs: 1748-6041

Abstract

Abstract: 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 (AI) 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 AI. Particularly, we explore AI 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 AI in cancer, diabetes, and neurological disorder therapy.