Large Language and Vision Assistant in dermatology: a game changer or just hype?
Abstract The integration of artificial intelligence (AI) in healthcare, particularly in the field of dermatology, has experienced significant progress through the creation of advanced tools such as the Large Language and Vision Assistant (LLaVA). This comprehensive review examines whether LLaVA repr...
Saved in:
| Published in: | Clinical and experimental dermatology Vol. 49; no. 8; pp. 783 - 792 |
|---|---|
| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
UK
Oxford University Press
19.07.2024
|
| Subjects: | |
| ISSN: | 0307-6938, 1365-2230, 1365-2230 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Abstract
The integration of artificial intelligence (AI) in healthcare, particularly in the field of dermatology, has experienced significant progress through the creation of advanced tools such as the Large Language and Vision Assistant (LLaVA). This comprehensive review examines whether LLaVA represents a significant breakthrough or merely a passing trend in dermatological practice. By incorporating both language and visual analysis capabilities, LLaVA aims to support enhanced diagnostic accuracy, patient engagement and customized treatment planning, as evidenced by current research and case studies. However, its practical utility in a clinical setting remains a subject of debate. We explore the visual assistant chatbot’s potential in improving diagnostic precision, especially in analysing skin lesions and conditions that are visually complex. The tool’s capacity to process and interpret dermatological images using advanced algorithms could aid clinicians in the early detection and management of skin diseases. Furthermore, LLaVA’s interactive nature potentially improves patient education and adherence to treatment protocols. Despite these advantages, there are noteworthy limitations and risks. The accuracy of LLaVA in handling atypical or rare dermatological cases is an area of concern. The tool’s reliance on existing medical data raises questions about bias and the generalizability of its findings. Additionally, ethical considerations, such as patient data privacy and the potential for overreliance on AI in clinical decision making, are critical issues that need addressing. This article aims to provide dermatologists with a comprehensive understanding of LLaVA’s capabilities and limitations. We discuss practical guidelines for its integration into research and clinical educational augmentation, ensuring that dermatologists can make informed decisions about employing this technology for the enhancement of patient care and treatment outcomes. The question remains: is LLaVA a game changer in dermatology, or is it just hype? This review endeavours to answer this, establishing a foundation for knowledgeable and efficient application of visual AI chatbots in dermatology practices.
The article emphasizes the role of AI chatbots, particularly the Large Language and Vision Assistant (LLaVA), in enhancing diagnostic accuracy and patient engagement in dermatology. It highlights the need for clinicians to be aware of the limitations and ethical considerations of AI tools, including LLaVA’s potential biases and diagnostic inaccuracies. Additionally, the article underscores LLaVA’s value as an educational resource for both clinicians and patients in understanding dermatological conditions and treatments, advocating for continued research and development to improve these AI tools’ reliability and effectiveness in dermatological applications. |
|---|---|
| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Review-3 content type line 23 |
| ISSN: | 0307-6938 1365-2230 1365-2230 |
| DOI: | 10.1093/ced/llae119 |