Integrating Artificial Intelligence in Indian Neurology: Recent Advances and Ethical Imperatives

Sir, The field of neurology in India is experiencing a swift embrace of technology, especially with artificial intelligence (AI) making waves in diagnostics, prognostication, and healthcare policy. A recent systematic review published in Neurology India looked into the diagnostic and predictive capabilities of machine learning (ML) and AI algorithms for meningoencephalitis, showcasing the increasing importance of AI in tackling infectious neurological disorders.1 Other articles, like “AI: From Artificial to Absolute – The Evolution of Intelligence” and “Artificial Intelligence Tools in Medical Writing – Boon or Bane?”, highlight the growing fascination with AI among both clinical and academic neurologists.2 AI has the potential to significantly improve access to neurological care in India. With around 1.8 million new stroke cases each year and a shortage of neurologists in rural areas, AI-powered imaging tools for early stroke detection can facilitate timely triage and referrals. Likewise, AI-enhanced EEG spike detection can help minimize reporting delays in epilepsy, which affects about 12 million people in India.3 Pilot projects at leading centers, like NIMHANS in Bengaluru and Apollo Hospitals, have started using AI-assisted neuroimaging and cognitive assessment platforms, proving that integrating AI into clinical practices is possible, although scaling this to district-level hospitals still poses a challenge.4 Even with all the progress we have made, there are still quite a few hurdles to overcome. A lot of AI models are built using data from populations that do not truly represent the rich genetic, environmental, and cultural diversity of India, which raises some serious questions about how accurate these diagnoses can be.5 In 2023, the ICMR rolled out ethical guidelines for AI in health care, and the Digital Personal Data Protection (DPDP) Act, 2023 set up a framework for how patient data can be used. However, when it comes to specific protocols for neurology, we are still lacking. Another big issue is medicolegal accountability: If an AI-assisted prediction goes wrong, it is unclear who should take responsibility—whether it is the clinicians, the institutions, or the software developers.4,5 To make sure we integrate AI responsibly into Indian neurology, I suggest we take the following steps: Create diverse neurological datasets that reflect India’s geographical and socioeconomic variety, with secure and open-access protocols. Develop institutional guidelines to validate AI/ML models within local populations before they are used in clinical settings. Improve physician understanding of AI, focusing on the limitations of algorithms, potential biases, and ethical issues. Set up oversight mechanisms that bring together medical, ethical, and legal expertise to keep an eye on AI applications and clarify liability frameworks. AI is paving the way for a new era in personalized neurological care. By bringing together various types of data—like imaging, genetics, and clinical history—AI can help create tailored treatment plans and predictive models.2-5 This is especially important for complex neurodegenerative diseases such as Parkinson’s and multiple sclerosis, where early intervention and customized therapies can make a real difference in patient outcomes. Additionally, predictive modeling can enhance how hospitals allocate resources, ensuring that critical care is directed to those who need it most.4,5 For this to work sustainably, it is essential for AI developers, neurologists, and public health officials to collaborate closely. By forming cross-disciplinary partnerships, we can make sure that AI solutions are not only clinically relevant but also culturally sensitive and adaptable to various healthcare environments in India. Encouraging innovation through grants and public-private partnerships, along with comprehensive training programs for healthcare professionals, will help close the knowledge gap and ensure that AI-enhanced neurological care is accessible to both urban and rural communities.1,3,5 In summary, AI in neurology has transitioned from a hopeful concept to a practical reality in India. To harness its full potential while avoiding any unintended pitfalls, we must ensure that innovation goes hand in hand with ethical governance, context-specific validation, and fair access for all. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.