Abstract

The currently growing field of health care and diagnostics is artificial intelligence. AI is becoming the primary tool for diagnosing a variety of illnesses, including neurological problems, thanks to its advanced algorithms. AI is transforming the early diagnosis of neurological disorders by making it possible to analyze complicated data in a precise, quick, and scalable manner. With the help of AIpowered algorithms, medical imaging, including MRI and CT scans, may be analyzed with surprising precision to find early indicators of diseases including multiple sclerosis, Parkinson’s disease, and Alzheimer’s disease often before symptoms appear. To find minute patterns connected to the start of disease, machine learning algorithms also analyze enormous datasets from genetic data, wearable technology, and electronic health records (EHRs). For instance, NLP techniques can examine a patient’s handwriting or speech to find early indicators of motor deficits or cognitive decline. Because AI-driven systems can identify trends in symptoms and biomarkers, they also improve diagnostic accuracy in less frequent illnesses like autoimmune encephalitis. For individuals with neurological disorders, artificial intelligence (AI) has the potential to greatly enhance outcomes by facilitating earlier intervention and individualized treatment. AI has been used, for instance, to find particular genetic abnormalities or protein misfolding patterns that act as early diagnostic markers in rare neurodegenerative or autoimmune illnesses. AI speeds up the identification of these biomarkers, which improves treatment results for patients with uncommon and poorly understood diseases by increasing diagnosis accuracy and facilitating the creation of focused medicines.

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Funding