What were the AI studies in my latest Aesthetic Surgery Journal?

Posted on April 29, 2026

AI analysis is exploding in medicine

These are exciting times, and hopefully using machine learning and new technology will help us improve medicine.

What were the studies published in the latest Aesthetic Surgery Journal re: AI?

Deep Learning Based Ensemble Model for Automated Nasolabial Fold Severity Grading.

Deep Learning Based Model for Breast Implant Classification in Ultrasonography: A Multi-Institutional Model Development and Validation Study.

Quality and Reliability – OpenEvidence is better

I had to make a paragraph about this, because I love Open Evidence. Open Evidence is a Language Learning Model that was created specifically for physicians to make well informed clinical decisions. It connects with peer reviewed literature in real time. I personally love it because often there are studies outside of plastic surgery which are applicable to my practice but I wouldn’t have seen, as they are published in peer review journals of dermatology, ENT, or other specialties.  I love that Open Evidence is in real time and truly up to date, so we don’t have to wait for the delay for the information to come out in print.

This study found OE was better than ChatGPT, which is designed for general public consumption and takes its information from the public internet.

This concluded, “OpenEvidence generated materials of significantly higher quality and reliability.”

What does Dr. Greenberg think of AI in plastic surgery?

AI is the future. I think the studies above using machine learning and large scale analysis are going to make us plastic surgeons and the instruments we use better. It is going to bring a bit more “science” and analysis into what we do, and a little less art and guesswork/experience.

For you, the patient, it could make surgery more consistent and precise. It may make who you go to less important, as tools may help diagnose and treat in a way that experience in the past guided us.

But AI models are not all equal (see my prior blog). AI can harvest bad information and data, which should not be used. AI also seems to have confirmation bias, where it tends to agree with the user.

Medical Citations

A Deep Learning–Based Ensemble Model for Automated Nasolabial-Fold Severity Grading, Aesthetic Surgery Journal Feb 2026

Deep Learning-Based Model for Breast Implant Classification in Ultrasonography: A Multi-Institutional Model Development and Validation Study , Aesthetic Surgery Journal, Feb 2026

Evaluating the Quality and Reliability of Large Language Models for Plastic Surgery Patient Education: A Comparative Analysis of ChatGPT and OpenEvidence, Aesthetic Surgery Journal Feb 2026


The information provided on this website is for general informational purposes only and does not constitute medical advice, diagnosis, or treatment. Always seek the advice of a qualified healthcare provider for any questions regarding your health or medical condition.

This blog has been authored by Dr. Lauren Greenberg

Dr. Lauren Greenberg is a Stanford-trained, board-certified plastic surgeon who brings over two decades of experience and a strong commitment to natural-looking results. She is known for combining advanced techniques with an honest, thoughtful approach to help patients feel confident and empowered.

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