Lily Huo

The first author, Miriam Leiko Terabe, is incorrectly noted as the corresponding author. The correct corresponding authors are João Ricardo Vissoci and Catherine Ann Staton. João Ricardo Vissoci’s email address is jnv4@duke.edu and Catherine Ann Staton’s email address is catherine.lynch@duke.edu. Reference 1. Terabe ML, Massago M, Iora PH, Hernandes Rocha TA, de Souza JVP, Huo L, et al. (2023) Applicability of machine learning technique in the screening of patients with mild traumatic brain injury.

PLOS ONE, Aug 2023 Even though the demand of head computed tomography (CT) in patients with mild traumatic brain injury (TBI) has progressively increased worldwide, only a small number of individuals have intracranial lesions that require neurosurgical intervention. As such, this study aims to evaluate the applicability of a machine learning (ML) technique in the screening of patients with mild TBI in the Regional University Hospital of Maringá, Paraná state, Brazil.

Discussion Research focused on developing better performing prognostic methods has increased due to scientific advancements and the emerging use of machine learning (ML) algorithms. However, gaps in literature indicate that ML has not been used in screening patients with mild TBI specifically in developing countries. Hence, we aimed to fill that gap by examining the performance of six classification supervised ML algorithms.