Evidence map›Paper›PMID 39971765›Full record

ArticleAesthetic plastic surgery2025

Response to the Comment on "Text-to-Video Models and Sora in Plastic Surgery: Pearls, Pitfalls, and Prospectives".

Yuanbo Kang, Sifan Wang, Lin Zhu

Abstract readLetterComment
PubMed Publisher
In one paragraph

Article in Aesthetic plastic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Yuanbo KangDepartment of Plastic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan 1#, Dongcheng District, Beijing, 100730, People's Republic of China.
Sifan WangDepartment of Plastic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan 1#, Dongcheng District, Beijing, 100730, People's Republic of China.
Lin ZhuDepartment of Plastic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan 1#, Dongcheng District, Beijing, 100730, People's Republic of China. pumchzhulin@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this paper is to respond to the comment regarding "Text-to-Video Models and Sora in Plastic Surgery: Pearls, Pitfalls, and Prospectives" and to provide further explanation on the opinions discussed therein. The emergence of text-to-video models, like Sora, allows us to see more vivid examples of artificial intelligence applied to life. The development of new technologies, like text-to-video models, needs to be recognized, questioned, regulated, and upgraded. We believe that the current problems of text-to-video models can be solved in the orderly development of the future, and the professional version of text-to-video models for practitioners in different industries will be more convenient for the liberation of productivity and the dissemination of corresponding professional knowledge.Level of Evidence V This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Indexed as

Artificial IntelligencePlastic Surgery ProceduresSurgery, PlasticVideo RecordingHumans

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.