AI-powered Nano-robots in Healthcare: Revolutionizing Internal Diagnostics and Treatment Delivery

AI nano-robots will revolutionize health care in the near future by integrating artificial intelligence into nanotechnology for advanced diagnostics and treatment delivery inside the body. The study looks at how these nano-robots enhance the circle of precision, efficiency, and personalization in healthcare related to early disease diagnosis, targeted drug delivery, and continuous health monitoring. This research, through a mixed-methods approach including systematic literature reviews, expert interviews, and advanced simulations, shows that AI guided nano-robots significantly outperform traditional approaches in navigation efficiency, early cancer detection (AUC: 0.97), and drug delivery efficacy by reducing side effects as high as 83%. This points toward new possibilities for proactive, personalized medicine and a shift in the healthcare ecosystem with nano-robots. Yet, it has to meet challenges like biocompatibility, ethical concerns, and equity of access. This study highlights the need for interdisciplinary collaboration, robust regulatory frameworks, and continued research on molecular-level disease interception and treatment to ensure successful translation into mainstream healthcare.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-15
DOI
https://doi.org/10.5281/zenodo.14837281
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
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article

AI-powered Nano-robots in Healthcare: Revolutionizing Internal Diagnostics and Treatment Delivery

1 citations
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
0.65
article

AI-powered Nano-robots in Healthcare: Revolutionizing Internal Diagnostics and Treatment Delivery

article en
1 citations

Abstract

AI nano-robots will revolutionize health care in the near future by integrating artificial intelligence into nanotechnology for advanced diagnostics and treatment delivery inside the body. The study looks at how these nano-robots enhance the circle of precision, efficiency, and personalization in healthcare related to early disease diagnosis, targeted drug delivery, and continuous health monitoring. This research, through a mixed-methods approach including systematic literature reviews, expert interviews, and advanced simulations, shows that AI guided nano-robots significantly outperform traditional approaches in navigation efficiency, early cancer detection (AUC: 0.97), and drug delivery efficacy by reducing side effects as high as 83%. This points toward new possibilities for proactive, personalized medicine and a shift in the healthcare ecosystem with nano-robots. Yet, it has to meet challenges like biocompatibility, ethical concerns, and equity of access. This study highlights the need for interdisciplinary collaboration, robust regulatory frameworks, and continued research on molecular-level disease interception and treatment to ensure successful translation into mainstream healthcare.

Zenodo (CERN European Organization for Nuclear Research)
Good health and well-being
Openalex Percentile: Top 19%
Artificial Intelligence in Healthcare and Education
0.65
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