Artificial Intelligence in Botulinum Toxin Injections: A Mini-Review of Current Applications, Challenges, and...

Area of Science:

• Medical Technology
• Artificial Intelligence in Medicine
• Dermatology and Neurology

Background:

• Botulinum toxin (BoNT) injections are crucial in aesthetic, surgical, and neurological fields.
• Current BoNT treatment relies heavily on clinician expertise and experience.
• Objective assessment and personalized treatment planning remain challenges.

Purpose of the Study:

• To review emerging artificial intelligence (AI) applications in botulinum toxin (BoNT) practice.
• To explore how AI can support various stages of the BoNT treatment pathway.
• To provide a structured overview of AI's potential role in clinical decision-making.

Main Methods:

• Literature review of PubMed-indexed and related peer-reviewed studies.
• Synthesis of representative AI applications across the BoNT treatment continuum.
• Analysis of AI's role in facial analysis, treatment simulation, and outcome assessment.

Main Results:

• AI tools show promise in areas like chatbot-assisted planning, deep learning for facial expressions, and MRI-based response prediction.
• AI applications span from pre-treatment planning to post-treatment assessment.
• Current evidence is preliminary, with limitations in sample size and validation.

Conclusions:

• AI can potentially support and augment physician judgment in BoNT practice.
• Further research is needed, prioritizing prospective validation and physician-supervised implementation.
• AI holds promise for improving objective outcome assessment and personalized treatment strategies.