Enhancing Clinical Note Generation with ICD-10, Clinical Ontology Knowledge Graphs, and Chain-of-Thought Prompting Using GPT-4

French AI startup Mistral has launched the Devstral 2 coding model, which includes a laptop-friendly version optimized for software engineering tasks. This release follows the introduction of the Mistral 3 LLM family, aimed at enhancing local hardware capabilities for developers.

Recent research has demonstrated the potential of Large Language Models (LLMs) in automating the generation of discharge summaries, which are critical documents in patient care. The study evaluated five models, including proprietary systems like GPT-4 and Gemini 1.5 Pro, and found that Gemini, particularly with one-shot prompting, produced summaries most similar to gold standards. This advancement could significantly reduce the workload of healthcare professionals and enhance the accuracy of patient information.

Large language models (LLMs) have revolutionized automated software development, enabling the conversion of natural language into functional code, as highlighted in a comprehensive survey on code intelligence. This evolution is exemplified by tools like Github Copilot and Claude Code, which have significantly improved coding success rates on benchmarks like HumanEval.