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record: TRV-2026-2161
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-10-22T10:42:24.488104Z
status: published
lens: trace
sector: health
headline: Artificial Intelligence in Plastic and Hand Surgery – Potential or Provocation?
dek: Introduction: Surgical specialities like plastic and hand surgery, which depend on precision, aesthetic, and functional outcomes, are integrating AI, creating potential and challenges. AI is rapidly transforming clinical procedures, requiring evaluation of its potential to improve clinical care and the challenges it faces. This narrative review critically evaluates the clinical applications, emerging innovations, and ethical challenges of AI in plastic and hand surgery, synthesising evidence on both its transfor…
gain_title: AI tools are being applied in plastic and hand surgery to classify skin lesions, evaluate aesthetics, and automate operative documentation, with further advances reported in microsurgery, simulation and rehabilitation.
problem_title: Use of AI in plastic and hand surgery still faces data bias, limited model interpretability, and unresolved liability and privacy concerns.
trace_subject: AI in plastic and hand surgery
gain_reading: AI tools are being applied in plastic and hand surgery to classify skin lesions, evaluate aesthetics, and automate operative documentation, with further advances reported in microsurgery, simulation and rehabilitation.
gain_evidence: classify skin lesions, evaluate aesthetics, and automate operative documentation
problem_reading: Use of AI in plastic and hand surgery still faces data bias, limited model interpretability, and unresolved liability and privacy concerns.
problem_evidence: significant challenges remain, including data bias, limited AI model interpretability, and concerns about liability and privacy
quick_read: A narrative review of peer-reviewed literature from 2018 to 2025, searched across PubMed, Scopus and Web of Science, examined how AI is entering plastic and hand surgery. It describes uses such as lesion classification with convolutional neural networks, aesthetic evaluation, and automated operative documentation using large language models.

The review matters because these specialities depend on precision and on aesthetic and functional outcomes, so errors or opaque tools carry real consequences. Its authors say adoption depends on acceptance, education, interdisciplinary collaboration and ethical guidelines. As a narrative review, it does not measure the size of any clinical benefit.
limitation: The source is a narrative review rather than a quantified trial, and it reports no measured effect sizes. It names data bias, limited interpretability, liability and privacy as challenges that remain unresolved.
tag: Dual reading
key_points: The review searched PubMed, Scopus and Web of Science for literature published between 2018 and 2025. | Convolutional neural networks and large language models are described as classifying skin lesions, evaluating aesthetics and automating operative documentation. | Generative AI, mixed reality and predictive analytics are cited in microsurgery, patient-specific simulation and smart rehabilitation. | Data bias, limited interpretability, liability and privacy are named as significant remaining challenges.
rundown: The authors frame their work as a Potential vs Provocation review that addresses benefits and challenges together. They say it differs from existing syntheses by also proposing concrete implementation strategies for clinical practice.

Search keywords included artificial intelligence, machine learning, deep learning, plastic surgery, hand surgery, microsurgery and convolutional neural networks. Included studies covered clinical applications, technological innovations and ethical considerations.

The conclusion says AI has significant potential to strengthen surgeons. It adds that integrating it requires acceptance, education, interdisciplinary collaboration and ethical guidelines to manage this technological evolution.
sources:
- peer_reviewed | Jurnal Plastik Rekonstruksi | https://doi.org/10.14228/jprjournal.v13i2.48 | 2026-10-21
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