Hybrid Machine Learning Methods and Ensemble Voting for Identification of Parkinson’s Disease Subtypes Published in “The Journal of Nuclear Medicine”. Original research from the TECVICO team: Purpose: It is important to subdivide Parkinson’s disease (PD) into specific subtypes, since homogeneous groups of patients are more likely to share genetic and pathological features, enabling potentially earlier disease recognition and more tailored treatment strategies. We aim to identify PD subtypes by using advanced hybrid machine learning (ML) methods followed by ensemble voting. Article Link: https://jnm.snmjournals.org/content/62/supplement_1/107 Join Tecvico projects: https://www.tecvico.com/projects/ Join us for more research! Contact us: 💚 Email: pr@tecvico.com 💚 WhatsApp: +1 (236) 515-1556