Researchers published a study in the journal Discover Computing demonstrating that artificial intelligence can identify Parkinson's disease with 99% accuracy by analyzing how patients draw simple figures. ^[1] A new study published in the scientific journal Discover Computing developed an artificial intelligence system capable of analyzing both the visual appearance of a drawing and the motor data of how it was drawn to detect signs of Parkinson's disease. ^[2] The AI system achieved a precision of 98.95% when analyzing meander patterns and 97.74% when analyzing spirals, combining both visual and invisible motor data. ^[3] Participants used a specialized digital pen to draw spirals and continuous angular lines, which recorded pressure, tilt, acceleration, and other hand movement characteristics. ^[4] The AI system analyzed the shape of drawings and movement data to identify small line deviations, tremor signs, pressure changes, and coordination disruptions that are difficult for humans to detect. ^[5] The study utilized data from 66 participants, consisting of 31 individuals diagnosed with Parkinson's disease and 35 healthy controls. ^[6] Researchers explicitly stated that individuals cannot diagnose Parkinson's disease by drawing a spiral at home based on these results. ^[7] The study concludes that the tool should be considered a computational research tool and not a substitute for a neurological evaluation. ^[8]