Publications by authors named "F Trabalzini"
Among acute mastoiditis (AM) complications, cerebral venous sinus thrombosis (CVST) is particularly severe, leading to increased intracranial pressure and potential neurological sequelae. Predicting the development of such complications is challenging. The aims of the present study were to evaluate the incidence, clinical characteristics, and risk factors for the development of CVST in AM.
View Article and Find Full Text PDFQuality of Information Provided by Artificial Intelligence Chatbots Surrounding the Reconstructive Surgery for Head and Neck Cancer: A Comparative Analysis Between ChatGPT4 and Claude2.
Clin Otolaryngol
December 2024
Introduction: Artificial Intelligences (AIs) are changing the way information is accessed and consumed globally. This study aims to evaluate the information quality provided by AIs ChatGPT4 and Claude2 concerning reconstructive surgery for head and neck cancer.
Methods: Thirty questions on reconstructive surgery for head and neck cancer were directed to both AIs and 16 head and neck surgeons assessed the responses using the QAMAI questionnaire.
Introduction: The recent approval of Dupilumab has profoundly revolutionized the management of patients affected by severe and recalcitrant Chronic Rhinosinusitis with Nasal Polyps (CRSwNP). However, a review that summarizes the results of real-life studies and compares them to phase 3 studies SINUS-24 and 52 is still lacking.
Materials And Methods: A search of all real-life studies published from 2019 to 2023 was performed.
Validation of the Quality Analysis of Medical Artificial Intelligence (QAMAI) tool: a new tool to assess the quality of health information provided by AI platforms.
Eur Arch Otorhinolaryngol
November 2024
Article Synopsis
- The study introduced the Quality Assessment of Medical Artificial Intelligence (QAMAI), a tool aimed at evaluating the quality of health information from AI platforms, highlighting the need for such assessments as AI use expands in healthcare.
- QAMAI was validated through a rigorous process involving 27 reviewers who evaluated responses generated by ChatGPT4, demonstrating strong reliability and validity metrics, including a high internal consistency (Cronbach's alpha = 0.837) and excellent inter-rater reliability (ICC = 0.983).
- The successful validation of QAMAI suggests it could be an important resource for healthcare professionals as more patients turn to AI for medical information, helping ensure they receive quality data.