ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026
Comment on "De Novo Reconstruction of 3D Human Facial Images from DNA Sequence".
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Reply to "Comment on 'De Novo Reconstruction of 3D Human Facial Images From DNA Sequence'".Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Moving the Fine Print to the Front Page: Transparent Communication of Facial Genetics Research.Advanced genetics (Hoboken, N.J.) · 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
Abstract
The recent article by Jiao et al., presenting the Difface model for reconstructing faces from deoxyribonucleic acid (DNA) and other artificial intelligence (AI)-enabled facial genetics research, has transformative potential for biomedical and forensic applications. Yet such research raises serious ethical, legal, and social challenges, as such applications are rights and safety impacting. Methodological transparency, algorithmic explainability, and contextualization of findings are essential to ensure that AI-enabled facial genetics research, such as Difface, is conducted responsibly and rigorously and interpreted reasonably. Given the lack of standards and benchmarks for DNA-based face generation, we use Difface as a case study to stress the need for transparent performance metrics and clear disclosure of data flows across AI training, validation, and testing pipelines-enabling non-experts to assess accuracy meaningfully.
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.