Artificial intelligence in trigeminal neuralgia and hemifacial spasm - De Bartolo Villar, Lautaro Ezequiel; Baldoncini, Matias; Campero, Alvaro (Revista Argentina de Neurocirugía, 2025)
Background: trigeminal neuralgia and hemifacial spasm are neurological disorders characterized by intense pain and involuntary muscle contractions, respectively. Both conditions are frequently diagnosed late due to inappropriate referrals, negatively impacting patients’ quality of life. Objectives: to develop and report two artificial intelligence (AI)-based applications aimed at assisting the diagnosis of trigeminal neuralgia and hemifacial spasm. Methods: two AI-based applications, "Trigeminal Neuralgia Diagnosis" and "Hemifacial Spasm Diagnosis," were developed. They were trained using 15 scientific articles, medical images, and iterative feedback cycles. The applications were evaluated by 150 participants (neurologists, neurosurgeons, dentists, and patients) through Google Forms surveys. Results: ninety-eight percent of neurosurgeons, 90% of neurologists and 92% of the dentists found the application useful. Regarding the intention to use, 96% of neurosurgeons, 88% of neurologists and 90% of dentists stated that they would use it. Patients reported a 92% satisfaction rate regarding ease of use, and 100% confirmed consistency between the diagnosis provided by the application and their previous medical diagnosis. Conclusion: AI-based applications demonstrated high acceptance and clinical usefulness, highlighting their potential for improving early diagnosis and appropriate referrals. Despite existing limitations in complex clinical scenarios, responsible integration of these applications could significantly enhance diagnostic efficiency and medical care quality, emphasizing the importance of considering ethical aspects.