Evidence map›Paper›PMID 41048541›Full record

ReviewBME frontiers2025

Sustainable Nanotechnology and Artificial Intelligence to Empower Image-Guided Therapy for Precision Healthcare.

Drishya Prakashan, Ramya Pr, Ajeet Kaushik, Sonu Gandhi

Abstract readReview
In one paragraph

Review in BME frontiers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Drishya PrakashanBRIC-National Institute of Animal Biotechnology (NIAB), Hyderabad 500032, Telangana, India.
Ramya PrBRIC-National Institute of Animal Biotechnology (NIAB), Hyderabad 500032, Telangana, India.
Ajeet KaushikNanoBioTech Laboratory, Department of Environmental Engineering, Florida Polytechnic University, Lakeland, FL, USA.
Sonu GandhiBRIC-National Institute of Animal Biotechnology (NIAB), Hyderabad 500032, Telangana, India.ORCID https://orcid.org/0000-0003-0960-2780

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanotechnology has substantially advanced imaging, therapy, and clinical techniques, playing a crucial role in the development of sustainable functional materials in biomedical engineering. Nanoparticles, used as contrast agents in multimodal imaging, offer notable advantages due to their high surface area-to-volume ratio, enabling functionalization with targeting ligands for improved specificity and sensitivity. They can also carry multiple imaging agents or therapeutic drugs, promoting theranostics, an approach combining diagnosis and treatment. However, the need for high-dose contrast agents raises concerns about nanoparticle toxicity. Green nanotechnology addresses this by developing sustainable nanoparticles through eco-friendly synthesis methods, reducing environmental and health risks. Moreover, by using this method, safer imaging agents that align with current health standards can be generated. In parallel, recent advancements in artificial intelligence (AI) are transforming imaging applications. Beyond simple automation of image interpretation, AI is enhancing image acquisition, management, and interpretation, signaling a future where intelligent systems play a key role in healthcare. This review explores the diverse nanomaterials utilized as contrast agents in multimodal imaging, highlights the importance of green nanotechnology in minimizing toxicity, and emphasizes on the important role of AI in imaging and image-guided therapy. Together, these innovations are advancing precision healthcare, promising a future where diagnostics and treatment are not only more effective but also sustainable.

Identifiers

PMID41048541
PMCPMC12494091

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.