UCD School of Computer Science, University College Dublin, Dublin, Ireland.
School of Medicine, Department of Dermatology, Hacettepe University, Ankara, Turkey.
Clin Exp Dermatol. 2024 Jul 19;49(8):783-792. doi: 10.1093/ced/llae119.
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.
人工智能(AI)在医疗保健领域的融合,特别是在皮肤病学领域,通过创建高级工具如大型语言和视觉助理(LLaVA)取得了显著进展。本综合综述考察了 LLaVA 是否代表了皮肤病学实践中的重大突破还是仅仅是一种流行趋势。通过结合语言和视觉分析能力,LLaVA 旨在支持提高诊断准确性、患者参与度和定制治疗计划,这一点可以从当前的研究和案例研究中得到证明。然而,它在临床环境中的实际效用仍然存在争议。我们探讨了视觉助手聊天机器人在提高诊断精度方面的潜力,特别是在分析视觉复杂的皮肤病变和情况方面。该工具使用先进算法处理和解释皮肤科图像的能力可以帮助临床医生早期发现和管理皮肤疾病。此外,LLaVA 的交互性质有可能改善患者的教育和治疗方案的依从性。尽管有这些优势,但也存在值得关注的局限性和风险。LLaVA 在处理非典型或罕见皮肤病病例方面的准确性是一个令人关注的问题。该工具对现有医疗数据的依赖引发了关于其发现的偏见和普遍性的问题。此外,患者数据隐私和在临床决策中过度依赖人工智能等伦理问题是需要解决的关键问题。本文旨在为皮肤科医生提供对 LLaVA 的能力和局限性的全面了解。我们讨论了将其集成到研究和临床教育中的实用指南,以确保皮肤科医生能够做出明智的决策,利用这项技术增强患者护理和治疗效果。问题仍然存在:LLaVA 是否是皮肤病学的游戏规则改变者,还是只是炒作?本综述旨在回答这个问题,为皮肤科实践中视觉 AI 聊天机器人的知识和高效应用奠定基础。