ArticleJournal of healthcare engineering2021
Value of ddPCR in the Preoperative Diagnosis of Solitary Pulmonary Nodules Based on the Observation of Virtual Reality Images of Smart Medical Treatment.
Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 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
3 citing papers in PubMed, 3 citations in OpenAlex.
- Retractions in tuberculosis research: analyzing patterns, reasons, and temporal trends from 1993 to 2023.Archives of microbiology · 2026Article
- Retracted: Value of ddPCR in the Preoperative Diagnosis of Solitary Pulmonary Nodules Based on the Observation of Virtual Reality Images of Smart Medical Treatment.Journal of healthcare engineering · 2023Article
- The Role of Three-Dimensional Reconstruction of Medical Images and Virtual Reality in Nursing Experimental Teaching.Journal of healthcare engineering · 2022Article
Corrections and comments
- Retraction · 2023-06-21Concerns/Issues about Data · Concerns/Issues about Human Subject Welfare · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Lack of IRB/IACUC Approval and/or Compliance · Unreliable Results and/or Conclusions · · See also: https://pubpeer.com/publications/48FA467965B3140F8D8F60341845E0
- Retracted
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
At present, lung cancer ranks the first cause of tumor death in the world, and malignant tumors in the SPN detected by imaging account for 5-40%, most of which are peripheral lung cancer. The recovery of the solitary nodules in the lung after treatment has also been paid attention to. In order to explore the correlation of solitary pulmonary nodule (SPN) with microvessel density (MVD), vascular parameters, and vascular ratio under virtual reality images of smart medical treatment and evaluate the differentiation of SPN by ddPCR under virtual reality image observation diagnosis value, this article collects relevant information by investigating patients, investigating relevant literature, interviewing professionals, and constructing a case template, using a comprehensive quantitative and qualitative analysis method to create a damage assessment matrix. Experimental results prove that there are significant differences in the microvascular architecture within the SPN in the benign, inflammatory, and malignant groups. The correlation between ddPCR and vascular parameters (especially the ratio of luminal vessels) under the virtual reality image observation of smart medical treatment is better than other detection methods, and its accuracy is about 10% higher. Based on the observation of smart medical virtual reality images, ddPCR can be used as an index for noninvasive evaluation of tumor angiogenesis, which is helpful for the differential diagnosis of SPN.
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.