Anghelescu Aurelian, Munteanu Constantin, Spinu Aura, Ciobanu Vlad, Popescu Cristina, Cioca Ioana Elena, Andone Ioana, Stoica Simona-Isabelle, Mandu Mihaela, Rebedea Ana, Giuvara Sebastian, Malaelea Alin-Daniel, Vladulescu-Trandafir Andreea-Iulia, Morcov Maria-Veronica, Onose Gelu
Department of Specific Discipline, Faculty of Midwifery and Nursing, University of Medicine and Pharmacy "Carol Davila", Bucharest, Romania.
Teaching Emergency Hospital "Bagdasar-Arseni", Bucharest, Romania.
Front Med (Lausanne). 2025 Jun 13;12:1565275. doi: 10.3389/fmed.2025.1565275. eCollection 2025.
INTRODUCTION: Considering the extensive development of artificial intelligence (AI) facilities, like Generative Pre-Trained Transformer (ChatGPT) 4.o and ChatGPT Scholar, we explored their abilities to conduct a systematic literature review. Using as a specific domain, an attempt to frame/methodize clinical assessment instruments used to evaluate neuro-functional deficits in Parkinson's disease (PD) - including framed through the ICF(-DH) paradigm - for the above-mentioned comparison between human intelligence (HI) and AI, this paper is as well, a follow-up regarding the most actual subject matter of the AI's capabilities evolution in this respect. As well-known clinical-/paraclinical-/functional evaluations, using assessment quantitative (as much as possible) instruments, are basic endeavors for rehabilitation, as they enable setting of appropriate and realistic therapeutic-rehabilitative specific goals. METHODS: Within the actual work, we have first achieved a narrative synthesis of the main molecular mechanisms involved in PD pathophysiology, underpinning its clinical appearance and evolution. To fundament our knowledge on an up-to-date information regarding the clinical-functional evaluation tools practiced in PD, we systematically reviewed the literature in this domain, published in the last 6 years, through a PRISMA type method for filtering/selecting the related bibliographic resources. The same keywords combinations/syntaxes have been used contextually, also to dialogize with ChatGPT4.o and ChatGPT. RESULTS: Scholar Applying PRISMA type methodology (HI achieved), we have selected, matching the filtering criteria, 24 articles. Interrogating the two AI above-mentioned models, we obtained quite difficult to be availed/useful - comparative to our HI obtained - outcomes. Thus, when interrogating ChatGPT4.o, ChatGPT Scholar repeatedly, they provided - partially diverse - inappropriate related answers, including ones pending on the interrogator's IP, although they claimed to have this capacity. DISCUSSION: We consider, regarding their capabilities to achieve systematic literature reviews, that neither ChatGPT 4.o nor ChatGPT Scholar still cannot succeed this (yet, they keep improving lately). Additionally, we have consistently extended, including within a narrative related literature review, our 'dialogue" with these two AI facilities regarding their availability to enhance the related evaluation instruments accuracy on neurofunctional assessments within biomarker-based frameworks. So, our research aimed basically to emphasize the main topical data regarding these two important paradigms of knowledge (based on HI and on AI) acquirements - considering the impetuous development of the latter - and thus, possibly to contribute inclusively at improving the actual performances to achieve Systematic Literature Reviews through the PRISMA type method - for the moment still better served by HI.
引言:鉴于人工智能(AI)工具的广泛发展,如生成式预训练变换器(ChatGPT)4.0和ChatGPT Scholar,我们探讨了它们进行系统文献综述的能力。作为一个特定领域,我们试图构建/规范用于评估帕金森病(PD)神经功能缺损的临床评估工具——包括通过国际功能、残疾和健康分类(ICF-DH)范式进行构建——以便在人类智能(HI)和AI之间进行上述比较。本文也是关于AI在这方面能力演变的最前沿主题的后续研究。众所周知,使用评估定量(尽可能)工具进行临床/准临床/功能评估是康复的基本工作,因为它们能够设定适当和现实的治疗康复具体目标。 方法:在实际工作中,我们首先对PD病理生理学中涉及的主要分子机制进行了叙述性综合,这些机制是其临床表现和演变的基础。为了基于有关PD中实践的临床功能评估工具的最新信息来巩固我们的知识,我们通过一种PRISMA类型的方法对过去6年发表的该领域文献进行了系统综述,以筛选/选择相关的文献资源。在上下文中使用了相同的关键词组合/语法,也用于与ChatGPT4.0和ChatGPT进行对话。 结果:应用PRISMA类型方法(人类智能完成),我们筛选出符合筛选标准的24篇文章。询问上述两个AI模型时,与我们人类智能获得的结果相比,我们得到的结果很难有用。因此,当反复询问ChatGPT4.0和ChatGPT Scholar时,它们提供了——部分不同的——不适当的相关答案,包括依赖询问者IP的答案,尽管它们声称具备这种能力。 讨论:关于它们进行系统文献综述的能力,我们认为ChatGPT 4.0和ChatGPT Scholar目前都无法成功做到这一点(不过,它们最近一直在改进)。此外,我们一直在扩展,包括在叙述性相关文献综述中,我们与这两个AI工具就它们在基于生物标志物的框架内提高神经功能评估相关评估工具准确性的可用性进行了“对话”。因此,我们的研究主要旨在强调关于这两种重要知识范式(基于人类智能和基于AI)获取的主要主题数据——考虑到后者的迅猛发展——从而可能全面有助于通过PRISMA类型方法提高实现系统文献综述的实际性能——目前人类智能在这方面仍然表现更佳。
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