ReviewDermatologie (Heidelberg, Germany)2026
[Artificial intelligence-based holistic, individualized facial analysis in aesthetic medicine].
Review in Dermatologie (Heidelberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aesthetic medicine is undergoing a substantial shift toward more objective, algorithm- and data-driven decision-making, with artificial intelligence (AI)-supported facial analysis playing a pivotal role. Modern systems such as CAARISMA™ capture the face holistically using anatomical landmarks, integrate these into the evaluation of different aesthetic dimensions, and translate them into easily interpretable scores such as Facial Aesthetic Index (FAI), Facial Youthfulness Index (FYI), and the Skin Quality Index (SQI). These indices enable standardized and reproducible aesthetic diagnostics, free from subjective, practitioner-specific influences. Clinically, they lead to more structured consultations, individualized treatment plans, and improved communication between physician and patient. At the same time, AI-based, data-driven aesthetic diagnostics and treatment planning can enhance efficiency and treatment quality in daily practice and allow for long-term monitoring of outcomes. Challenges at the interface between AI and aesthetics lie in the areas of bias, transparency, and data protection, all of which must be addressed to ensure responsible use of these technologies.
Indexed as
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41533081What 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.