Bonanno Mirjam, Cardile Davide, Liuzzi Piergiuseppe, Celesti Antonio, Micali Giuseppe, Corallo Francesco, Quartarone Angelo, Tomaiuolo Francesco, Calabrò Rocco Salvatore
IRCCS Centro Neurolesi "Bonino-Pulejo", Messina, Italy.
Department of Mathematics and Computer Sciences, Physical Sciences and Earth Sciences, University of Messina, Messina, Italy.
Front Artif Intell. 2025 May 30;8:1608778. doi: 10.3389/frai.2025.1608778. eCollection 2025.
Artificial intelligence (AI), in the form of machine learning (ML) or deep learning (DL) models, can aid clinicians in the diagnostic process and/or in the prognosis of critically medical conditions, as for patients with a disorder of consciousness (DoC), in which both aspects are particularly challenging. DoC is a category of neurological impairments that are mainly caused by severe acquired brain injury, like ischemic or hemorrhagic strokes or traumatic injuries. The aim of this scoping review is to map the literature on the role of ML and DL in the field of diagnosis and prognosis of DoCs.
A scoping search, started from 3rd October 2024, was conducted for all peer-reviewed articles published from 2000 to 2024, using the following databases: PubMed, Embase, Scopus and Cochrane Library.
We found a total of 49,417 articles. After duplicate removal and title/abstract screening, 613 articles met the inclusion criteria, but 592 articles were excluded after full-text review. Therefore, only 21 studies involving DoC subjects were included in the review synthesis.
Advancing AI in the field of DoC requires standardized data protocols and consideration of demographic variations. AI could enhance diagnosis, prognosis, and differentiation between states like unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS). Additionally, AI-based applications personalize rehabilitation by identifying key recovery factors, optimizing patient outcomes.
以机器学习（ML）或深度学习（DL）模型形式存在的人工智能（AI），可以在诊断过程中辅助临床医生，和/或对危重症患者进行预后评估，对于意识障碍（DoC）患者而言，这两个方面都极具挑战性。DoC是一类神经功能障碍，主要由严重的后天性脑损伤引起，如缺血性或出血性中风或创伤性损伤。本综述的目的是梳理有关ML和DL在DoC诊断和预后领域作用的文献。
从2024年10月3日开始进行范围检索，检索2000年至2024年发表的所有同行评审文章，使用以下数据库：PubMed、Embase、Scopus和Cochrane图书馆。
我们共找到49417篇文章。在去除重复文章并进行标题/摘要筛选后，613篇文章符合纳入标准，但在全文评审后排除了592篇文章。因此，本综述综合仅纳入了21项涉及DoC受试者的研究。
在DoC领域推进AI需要标准化的数据协议，并考虑人口统计学差异。AI可以加强诊断、预后评估，以及区分无反应觉醒综合征（UWS）和最小意识状态（MCS）等状态。此外，基于AI的应用程序通过识别关键恢复因素来实现个性化康复，优化患者预后。
