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A Review of Safety and Accuracy Follow Different Scaling Laws in Clinical Large Language Models The use of large language models (LLMs) in medical AI and clinical decision support systems (CDSS) is expanding rapidly. We often assume that larger models, longer context windows, more sophisticated retrieval, and greater inference-time compute will not only improve accuracy, but also make AI systems safer. But does higher average accuracy necessarily mean a model is clinically sa

The VETFR.AI.DAY Constitution by CHOONOK Company (This content was created with the assistance of AI.) CHOONOK Company has published the VETFR.AI.DAY Constitution, outlining the principles and limitations that guide its AI-powered clinical decision support system for small animal practice. The Constitution is not a document created to showcase AI performance. Instead, it was developed to clearly define how clinical AI should be designed for real-world veterinary practice—and

Choonok Company Maps Veterinary AI Use Into 3 Categories and 21 Query Types Choonok Company has released a preprint examining how veterinary professionals use AI across different stages of clinical practice. The study, titled “Development of an Exploratory Taxonomy for Veterinary Professionals’ AI Query Patterns Across Clinical Stages: An Expert Panel Study,” aimed to systematically classify AI queries in veterinary practice according to clinical stage and purpose. The paper

Performance Validated Using a Benchmark Based on Japan’s National Veterinary Licensing Examination 춘옥컴퍼니 임직원 Choonok Company has unveiled VetJarvis-4B-Instruct, a generative large language model (LLM) specialized for the veterinary domain, marking a new milestone in the development of veterinary AI for research and education. The release demonstrates that a generative AI model built around veterinary knowledge can achieve meaningful performance in professional knowledge asses