Democratizing cost-effective, agentic artificial intelligence to multilingual medical summarization through knowledge distillation

• Published in: Scientific reports Vol. 15; no. 1; pp. 27619 - 10
• Main Authors: Lee, Chanseo, Kumar, Sonu, Vogt, Kimon A., Munshi, Muhammad, Tallapudi, Panindhra, Vogt, Antonia, Awad, Hamzeh, Khan, Wasim
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 29.07.2025; Nature Publishing Group; Nature Portfolio
• Subjects: 639/705/1046; 639/705/117; 639/705/794; 692/700; 692/700/3934; Accuracy; AI Agents; Artificial Intelligence; Clinical Documentation; Cost-Benefit Analysis; Datasets; Distillation; Documentation; Health care; Human subjects; Humanities and Social Sciences; Humans; Knowledge; Knowledge Distillation; Language; Large language models; Learning; multidisciplinary; Multilingualism; Personal information; Regularization methods; Science; Science (multidisciplinary); Small Language Models (SLMs); Sustainability in AI; Terminology; Verbal communication; Knowledge Distillation; Sustainability in AI; Small Language Models (SLMs); Clinical Documentation; AI Agents; Artificial Intelligence

The increasing demand for multilingual capabilities in healthcare technology highlights the critical need for AI solutions capable of handling underrepresented languages, such as Arabic, in clinical documentation. Arabic’s unique linguistic complexities—morphological richness, syntactic variations,...