Researchers from the University of Córdoba in Spain trained a deep-learning algorithm to evaluate a patient's potential presynaptic deficit on 3D SPECT images. In testing, the algorithm yielded a promising level of performance for classifying patients as either normal or in one of three other classes that indicate an increasing severity of brain damage. The information generated by AI of 3D SPECT could potentially enable physicians to adjust a patient's treatment based on the severity of their disease, according to researchers led by Javier Barbero-Gómez. "These methods could help doctors in the diagnosis and treatment of [Parkinson's disease] and other parkinsonisms through [decision-support systems] and contribute toward the relief of the public health cost of this disease," the authors wrote.