A study published in the latest issue of Nature Chemical Engineering suggests that an artificial intelligence (AI) pen equipped with magnetic ink can accurately "read words and be used to assist in detecting early symptoms of Parkinson's disease. This device uses neural networks to assist in data analysis and can identify the differences in writing characteristics between Parkinson's disease patients and healthy individuals, which is expected to achieve earlier diagnosis. Parkinson's disease is estimated to affect nearly 10 million people worldwide and is the second most common neurodegenerative disease after Alzheimer's disease. Parkinson's disease is also the fastest-growing neurodegenerative disease globally, especially in low - and middle-income countries. It is currently widely believed that the number of Parkinson's disease diagnoses is severely underestimated, partly due to a lack of trained medical professionals in these countries to diagnose the disease. Moreover, the early symptoms of this disease are insidious and easily confused with other motor disorders, so accurate diagnosis is crucial for timely intervention and improving patients' quality of life. Due to symptoms such as tremors, doctors typically diagnose the disease based on observing the patient's motor skills. However, this method lacks objective standards and often relies on the subjective judgment of clinical doctors. The team led by Jun Chen from the University of California, Los Angeles has developed a method for diagnosing Parkinson's disease by analyzing samples written with customized pens containing magnetic ink. They converted writing movements into electrical signals and used neural networks (an AI method that learns and distinguishes complex patterns through interconnected node networks) to analyze and demonstrate that the pen can distinguish writing features between Parkinson's disease patients and healthy individuals with over 95% accuracy in a small-scale queue of 16 patients. The emergence of this diagnostic pen represents a low-cost, accurate, and easily distributable technology, which is expected to improve the diagnosis of Parkinson's disease in large-scale populations and resource scarce areas. Researchers point out that future work is to expand the patient sample size of the tool and explore its potential in tracking the progression stages of Parkinson's disease. (New Society)