What ChatGPT and generative AI mean for science

By Chris Stokel-Walker, Richard van Noorden. Nature, 2023

689 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Health Informatics, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/5f996fd3592478b6923590ed5347d6206357e95a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. S. Reddy
2. Siqi Sun

In Health Informatics

1. S. Reddy

In Radiology, Nuclear Medicine and Imaging

1. S. Reddy

Citations in the corpus

• The future landscape of large language models in medicine (2023, background): “However, while they have the potential to democratize access to scienti fi c evidence, they could result in misinformation and facilitate scienti fi c misconduct 44 – 46 .”
• A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development (2023, background): “Till now, ChatGPT/GPT4 has shown promising performance as a general purpose multimodal task-solver [30], which has been widely used in the field of we-media, data analysis, etc.”
• Generative AI in healthcare: an implementation science informed translational path on application, integration and governance (2024, methodology): “It is important to note that while LLMs are powerful, they have limitations [15].”