ReviewJournal of cosmetic dermatology2025
The Transformative Potential of AI in Ultrasound for Facial Aesthetics.
Review in Journal of cosmetic dermatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evaluation of Facial Artery Course Variations, Diameters, and Depth Using Doppler Ultrasonography: A Systematic Review and Meta-Analysis.Journal of cosmetic dermatology · 2025Pooled it
- Artificial Intelligence in Non-Surgical Cosmetic Procedures: A Multi-Stakeholder Revolution.Aesthetic plastic surgery · 2026Review
- Skin as a sentinel and modulator of systemic aging: a translational framework for evidence-based gerotherapeutics.GeroScience · 2026Review
- Review
- Closed-loop Energy-based devices in dermatology: moving from static protocols to smart skin.Lasers in medical science · 2025Article
- Article
- The SIBUS-IN Fingerheld Ultrasound Machine.Journal of cosmetic dermatology · 2025Article
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
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe integration of artificial intelligence (AI) and ultrasound (US) technology is reshaping facial aesthetics, providing enhanced diagnostic precision, procedural safety, and personalized patient care. The variability in US imaging, stemming from patient anatomy, operator skills, and equipment diversity, poses challenges in achieving consistent and accurate outcomes. AI addresses these limitations by standardizing imaging protocols, automating image analysis, and supporting real-time decision-making.
objectiveTo explore the applications of AI-enhanced US in facial aesthetics, focusing on its potential to improve diagnostic accuracy, procedural safety, and personalized treatments while identifying future prospects and challenges.
methodsA comprehensive review of current literature and advancements was conducted, examining the integration of AI with US in facial aesthetics. Key areas of focus included AI algorithms for image enhancement, real-time guidance during procedures, postprocedure assessment, personalized treatment planning, and workflow optimization.
resultsAI-enhanced US significantly improved diagnostic accuracy by automating the identification of critical anatomical structures and reducing operator variability. Real-time guidance during procedures enhanced safety, reducing complications such as vascular occlusion and nerve damage. Postprocedure assessments facilitated early detection of complications and improved patient outcomes. Personalized treatment plans tailored to individual anatomy and clinical needs resulted in higher patient satisfaction. Additionally, AI optimized workflow efficiency through seamless integration with electronic health records and advanced training simulators.
conclusionThe integration of AI and US technology represents a transformative advancement in facial aesthetics. By enhancing precision, safety, and personalization, AI-powered US sets new benchmarks in diagnostic accuracy and treatment outcomes. Despite challenges related to data diversity, ethical considerations, and training, this synergy holds immense potential to revolutionize the field, offering improved outcomes and satisfaction for practitioners and patients alike. Further research and innovation are essential to fully realize the benefits of this technology.
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.