ReviewSensors international2022
Sensing and 3D printing technologies in personalized healthcare for the management of health crises including the COVID-19 outbreak.
Review in Sensors international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 23 citations in OpenAlex.
- A Comparative Study of Commercial 3D Printers for Food Fabrication Based on Printing Ink Gels.Gels (Basel, Switzerland) · 2026Review
- Concept and Evolution in 3D Printing for Excellence in Healthcare.Current medicinal chemistry · 2025Review
- Recycled PETg embedded with graphene, multi-walled carbon nanotubes and carbon black for high-performance conductive additive manufacturing feedstock.RSC advances · 2024Article
- Antimicrobial and anti-viral effects of selenium nanoparticles and selenoprotein based strategies: COVID-19 and beyond.Journal of drug delivery science and technology · 2023Review
- Review
- Institutional Strategies to Maintain and Grow Imaging Research During the COVID-19 Pandemic.Academic radiology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A major threat that has surrounded human civilization since the beginning of the year 2020 is the outbreak of coronavirus disease 2019 (COVID-19). It has been declared a pandemic by the World Health Organization and significantly affected populations globally, causing medical and economic despair. Healthcare chains across the globe have been under grave stress owing to shortages of medical equipments necessary to address a pandemic. Furthermore, personal protective equipment supplies, mandatory for healthcare staff for treating severely ill patients, have been in short supply. To address the necessary requisites during the pandemic, several researchers, hospitals, and industries collaborated to meet the demand for these medical equipments in an economically viable manner. In this context, 3D printing technologies have provided enormous potential in creating personalized healthcare equipment, including face masks, face shields, rapid detection kits, testing swabs, biosensors, and various ventilator components. This has been made possible by capitalizing on centralized large-scale manufacturing using 3D printing and local distribution of verified and tested computer-aided design files. The primary focus of this study is, "How 3D printing is helpful in developing these equipments, and how it can be helpful in the development and deployment of various sensing and point-of-care-testing (POCTs) devices for the commercialization?" Further, the present study also takes care of patient safety by implementing novel 3D printed health equipment used for COVID-19 patients. Moreover, the study helps identify and highlight the efforts made by various organizations toward the usage of 3D printing technologies, which are helpful in combating the ongoing pandemic.
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.