Abstract The clinical evaluation of brain diseases strictly depends on patient’s complaint and observation of their behavior. The specialist, often the neurologist, chooses whether and how to assess cognition, motor system, sensory perception, and autonomic nervous system. They may also decide to request a more in-depth examination, such as neuropsychological and language assessments and imaging or laboratory tests. From the synthesis of all these results, they will be able to make a diagnosis. The neuropsychological assessment in particular is based on the collection of medical history, on the clinical observation, and on the administration of standardized cognitive tests validated in the scientific literature. It is therefore particularly useful when a neurological disease with cognitive and/or behavioral manifestation is suspected. The introduction of machine learning methods in neurology represents an important added value to the evaluation performed by the clinician to increase the diagnostic accuracy, track disease progression, and assess treatment efficacy.