ReviewCurrent drug targets2025
Role of Artificial Intelligence in Nanomedicine and Organ-specific Therapy: An Updated Review.
Review in Current drug targets, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Review
- Quantitative structure-activity relationship characterization and modeling of length-varying bioactive peptides.Journal of computer-aided molecular design · 2026Article
- Harnessing AI-driven approaches for detecting metabolic dysfunction-associated steatotic liver disease, assessing fibrosis, and stratifying hepatocellular carcinoma risk: a scoping review.Frontiers in oncology · 2026Review
- Tumor ecosystem subtyping of breast cancer based on somatic mutations and network propagation reveals distinct prognostic and genomic landscapes.Frontiers in genetics · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn organ-specific therapy, artificial intelligence (AI) is primarily used to improve surgical planning through image analysis, predict post-transplant outcomes, personalize treatment plans based on patient data, optimize organ allocation logistics, and donor-recipient precision mapping for organs to improve transplants. Furthermore, all these applications ultimately lead to better patient outcomes and enhanced organ therapy.
objectiveThis review aims to examine the revolutionary effects of AI in some key healthcare fields, such as nanomedicine, cancer treatment, clinical applications, and organ-specific delivery.
methodsThis review article discusses in detail the role of AI in nanomedicine, cancer therapy, clinical applications, organ-specific delivery (e.g., cardiovascular, gastroenterology, kidney, liver, lung, ophthalmology, skin, etc.), diagnosis, and radiotherapy. In addition, it also discusses limitations and challenges of AI in healthcare.
resultsAI-based clinical translation has potential but faces challenges like artifact vulnerability, ethical and legal considerations, and security measures. Restrictive data-use policies may hinder accurate analysis. Regulations and collaboration with data-sharing mechanisms could overcome barriers.
conclusionAI is being utilized in organ-specific therapy to enhance donor-recipient matching, surgical planning, post-transplant outcomes prediction, and personalized treatment plans by analyzing patient data.
Indexed as
Identifiers
40698694What Socratic holds
Registered trials
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.