Advancements in Brain Health Monitoring and Diagnosis Using Machine Learning and Artificial Intelligence Techniques

Abstract

The application of AI, and ML, technologies is about to change status quo across industries including healthcare. Although principal purpose of mentioned abstract to highlighting successful application of AI and machine learning in enhancing mental health, it revolved of quite a few key technologies. Particularly, around diagnosing, treating, and managing neurological disorders and brain diseases, the impact of the application of AI, and ML technologies has been revolutionary. They can track patterns, detect disease markers, and anticipate an illness's progression with outstanding accuracy using AI models trained on vast volumes of data. Additionally, like PET and FMRI actually Functional MRI imaging technologies enables accurate localization of neural functions and structural abnormalities allowing preliminary observation of neurological diseases and the development of tailored treatments. In addition, beyond the scope of diagnostics, AI-based predictive analytics has made it possible to design customized treatment programs and even prevent disease before it occurs not change the course of the disease. AI systems have the capability to include patient data like his/her genetics, sick history, and lifestyle factors to calculate risks for diseases concerning neurology and even assist doctors in risk-reducing specialized treatments and ensuring better results. So too, AI chat bots and virtual assistants have transformed patient support and engagement through provision of easily accessible information, resources and customized support for patients with neurologic illness and their caregivers round the clock and they also facilitate better communication. These digital companions promote autonomy and health of patients by providing psychological assistance, helping to adhere to a drug schedule, managing signs and even continuous observation of the patient. Even with the tremendous developments, the AI and ML technologies will not be used thoroughly in brain health with numerous barriers such as ethical boundaries, data privacy issues, and laws being obstacles to progress. The equitable availability of AI-assisted healthcare services and the just distribution of their effects are also strategic if the full potential of these technologies in enhancing brain health status around the globe is to be achieved.

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