REVIEW article
Front. Med.
Sec. Precision Medicine
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1599340
This article is part of the Research TopicNanomedicine Targeting Central Nervous SystemView all 4 articles
Artificial Intelligence (AI) Based Advancements in Nanomedicine for Brain Disorder Management: An Updated Narrative Review
Provisionally accepted
- 1National Institute of Nursing Research (NIH), Bethesda, Maryland, United States
- 2Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, College Park, Maryland, United States
- 3Division of Hematology and Oncology, Department of Medicine, School of Medicine, University of Missouri, Columbia, Missouri, United States
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Nanomedicines are nanoscale, biocompatible materials that offer promising alternatives to conventional treatment options for brain disorders. The recent technological developments in artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), are transforming the nanomedicine field by improving disease diagnosis, biomarker identification, prognostic assessment and disease monitoring, targeted drug delivery, and therapeutic intervention as well as contributing to computational and methodological developments. These advancements can be achieved by analysis of large clinical datasets and facilitating the design and optimization of nanomaterials for in vivo testing. Such advancement offers exciting possibilities for the improvement in the management of brain disorders, including brain cancer, Alzheimer's disease, Parkinson's disease, and multiple sclerosis, where early diagnosis, targeted delivery, and effective treatment strategies remain a great challenge. This review article provides an overview of recent advances in AI-based nanomedicine development to accelerate effective and quick diagnosis, biomarker identification, prognosis, drug delivery, methodological advancement and patientspecific therapies for managing brain disorders.
Keywords: artificial intelligence, Brain Disorders, deep learning, nanomaterial, machine learning, Nanomedicine
Received: 24 Mar 2025; Accepted: 15 Apr 2025.
Copyright: © 2025 Dipankar, Salazar, Dennard, Mohiyuddin and Nguyen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Quynh C Nguyen, National Institute of Nursing Research (NIH), Bethesda, 20892-2178, Maryland, United States
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