ReviewWiley interdisciplinary reviews. Nanomedicine and nanobiotechnology
Transforming Cancer Nanotechnology Data Analysis and User Experience. Part I: Current Challenges and Solutions Provided by caNanoLab.
Review in Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Nanomaterials in Drug Delivery: Leveraging Artificial Intelligence and Big Data for Predictive Design.International journal of molecular sciences · 2025Review
- Transforming Cancer Nanotechnology Data Analysis and User Experience. Part I: Current Challenges and Solutions Provided by caNanoLab.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Cancer nanotechnologies have the potential to revolutionize cancer diagnosis and treatment; however, their complexity poses challenges to data analysis and knowledge sharing. caNanoLab, a dedicated cancer nanotechnology data-sharing portal, has emerged as a valuable resource for researchers in this field. However, to fully utilize the wealth of data available in caNanoLab, there is a need for real-time descriptive statistical presentation and an optimized user experience. Herein, we provide an overview of cancer nanotechnologies and federally funded efforts to create data repositories, aiming to improve information flow and data sharing among researchers in the cancer nanotechnology field. We use caNanoLab as a case study to analyze the challenges in this area and highlight how caNanoLab addresses them. We also identify gaps and explore the potential of Large Language Models (LLMs) to improve user experience. A more detailed analysis of LLM and their applications to caNanoLab is provided in the second part of this review. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.