Revolutionizing radiology with GPT-based models: Current applications, future possibilities and limitations of ChatGPT.

By A. Lecler, L. Duron, P. Soyer. Diagnostic and Interventional Imaging, 2023

336 citations recorded by the source corpus.

Artificial intelligence has demonstrated utility and is increasingly being used in the field of radiology. The use of generative pre-trained transformer (GPT)-based models has the potential to revolutionize the field of radiology, offering new possibilities for improving accuracy, efficiency, and patient outcome. Current applications of GPT-based models in radiology include report generation, educational support, clinical decision support, patient communication, and data analysis. As these models continue to advance and improve, it is likely that more innovative uses for GPT-based models in the field of radiology at large will be developed, further enhancing the role of technology in the diagnostic process. ChatGPT is a variant of GPT that is specifically fine-tuned for conversational language understanding and generation. This article reports some answers provided by ChatGPT to various questions that radiologists may have regarding ChatGPT and identifies the potential benefits ChatGPT may offer in their daily practice but also current limitations. Similar to other applications of artificial intelligence in the field of imaging, further formal validation of ChatGPT is required.

Subfields: Artificial Intelligence, Health Informatics, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/eb9ab13a412befa0ac793cb510ea7a78b9881c5b

How researchers see this paper

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

In Artificial Intelligence

1. Thippa Reddy Gadekallu
2. Jan Egger
3. Gokul Yenduri
4. Jens Kleesiek
5. Praveen Kumar Reddy Maddikunta

In Health Informatics

1. Jan Egger
2. Jianning Li
3. Amin Dada
4. Jens Kleesiek
5. Behrus Puladi

In Radiology, Nuclear Medicine and Imaging

1. Thippa Reddy Gadekallu
2. Praveen Kumar Reddy Maddikunta

Citations in the corpus

• GPT (Generative Pre-Trained Transformer)— A Comprehensive Review on Enabling Technologies, Potential Applications, Emerging Challenges, and Future Directions (2023, background): “They can help with the article’s structure, writing the introduction, arranging the results, and discussing the conclusions [90].”
• ChatGPT in Healthcare: A Taxonomy and Systematic Review (2023, background): “[65] miscellaneous original article comments on the potential usage of ChatGPT in radiology (generate radiological reports, education, diagnostic decision-making, communicate with patients, compose radiological research article) Level 1”
• BioRAG: A RAG-LLM Framework for Biological Question Reasoning (2024, background): “However, this ever-changing landscape and the complex interplay between different knowledge components present obstacles (Lee et al., 2023; Castro Nascimento and Pimentel, 2023; Lecler et al., 2023; Song et al., 2020) in creating efficient domain-specific question-reasoning systems.”