What could we make of AI in plastic surgery education.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS 2023 Vol.81() p. 94-96

Koljonen V

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Abstract

To explore the possibilities of artificial intelligence (AI) text-to-picture system, DALL·E 2 was used to generated clinical photographs for medical and plastic surgery education. Generic English text was used to guide AI in three categories: subcutaneous tumor, wound and skin tumor. The most clinically accurate images were chosen for the article or for further editing. AI-generated images with variating clinical accuracy in different categories. The most accurate images were the soft-tissue tumors and the least accurate wounds. This study showed that AI text-to-picture system might be worthy tool for medical education.

추출된 의학 개체 (NER)

유형영어 표현한국어 / 풀이UMLS CUI출처등장
해부 subcutaneous 피하조직 dict 1
합병증 wound scispacy 1
합병증 wounds scispacy 1
질환 tumor C0027651
Neoplasms
scispacy 1
질환 tumors C0027651
Neoplasms
scispacy 1
질환 subcutaneous tumor scispacy 1
질환 skin tumor scispacy 1
질환 soft-tissue tumors scispacy 1

MeSH Terms

Humans; Artificial Intelligence; Surgery, Plastic; Plastic Surgery Procedures; Skin Neoplasms; Soft Tissue Neoplasms

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