ReviewBone research2022
Computer vision-aided bioprinting for bone research.
Review in Bone research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 29 citations in OpenAlex.
- Artificial Intelligence Informed Hydrogel Biomaterials in Additive Manufacturing.Gels (Basel, Switzerland) · 2025Review
- The Synergy of Artificial Intelligence and 3D Bioprinting: Unlocking New Frontiers in Precision and Tissue Fabrication.Advanced functional materials · 2025Article
- Comprehensive Analysis of Sialylation-Related Gene Profiles and Their Impact on the Immune Microenvironment in Periodontitis.Inflammation · 2025Article
- Nonlinear Harmonics: A Gateway to Enhanced Image Contrast and Material Discrimination.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Precision improvement of robotic bioprinting via vision-based tool path compensation.Scientific reports · 2024Article
- Multi-modal transcriptomics: integrating machine learning and convolutional neural networks to identify immune biomarkers in atherosclerosis.Frontiers in cardiovascular medicine · 2024Article
- Biomaterials / bioinks and extrusion bioprinting.Bioactive materials · 2023Review
- Error assessment and correction for extrusion-based bioprinting using computer vision method.International journal of bioprinting · 2023Article
- Uncovering the potential role of oxidative stress in the development of periodontitis and establishing a stable diagnostic model via combining single-cell and machine learning analysis.Frontiers in immunology · 2023Article
- Bioprinting extracellular vesicles as a "cell-free" regenerative medicine approach.Extracellular vesicles and circulating nucleic acids · 2023Review
- Bio-high entropy alloys: Progress, challenges, and opportunities.Frontiers in bioengineering and biotechnology · 2022Review
- Medical high-entropy alloy: Outstanding mechanical properties and superb biological compatibility.Frontiers in bioengineering and biotechnology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
Bioprinting is an emerging additive manufacturing technology that has enormous potential in bone implantation and repair. The insufficient accuracy of the shape of bioprinted parts is a primary clinical barrier that prevents widespread utilization of bioprinting, especially for bone design with high-resolution requirements. During the last five years, the use of computer vision for process control has been widely practiced in the manufacturing field. Computer vision can improve the performance of bioprinting for bone research with respect to various aspects, including accuracy, resolution, and cell survival rate. Hence, computer vision plays a substantial role in addressing the current defect problem in bioprinting for bone research. In this review, recent advances in the application of computer vision in bioprinting for bone research are summarized and categorized into three groups based on different defect types: bone scaffold process control, deep learning, and cell viability models. The collection of printing parameters, data processing, and feedback of bioprinting information, which ultimately improves printing capabilities, are further discussed. We envision that computer vision may offer opportunities to accelerate bioprinting development and provide a new perception for bone research.
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.