ANA-SEQUINS Health Services and Health Opportunities | Brain Health and Technology: Innovation, Equity, and Impact *
Date: October 18, 2026
Time: 3:30 pm to 5:00 pm
Room: Coral 1
Track: Cross-Cutting Special Interest Group (SIG)
Session Description
Rapid advances in digital health, artificial intelligence, and social media are transforming how brain health is understood, delivered, and promoted across the lifespan. However, without careful attention to access, ethics, privacy, and implementation, these innovations risk widening existing disparities. This session brings together leaders in technology, policy, and youth engagement to explore how emerging tools can be leveraged responsibly to advance equitable brain health worldwide.
The session will begin by examining the “great technology divide” in brain health, highlighting challenges and opportunities related to digital health platforms, wearables, and global health applications. Key topics will include electronic health record (EHR) integration, data overload, interoperability, privacy concerns, and real-world barriers to adoption across diverse healthcare settings. Dr. Adys Mendizabal will present on the future of digital health and AI for brain health.
Dr. Baibing Chen will explore strategies to empower youth to take an active role in managing and promoting their brain health. The session will conclude with a forward-looking, policy-focused discussion on the ethical development and implementation of AI in brain health. Dr. Amy Guzik will examine frameworks to ensure AI-driven tools enhance clinical care without reinforcing bias, compromising trust, or excluding vulnerable populations, with an emphasis on governance, regulation, and cross-sector collaboration.
Overall, this session will provide clinicians, researchers, policymakers, and innovators with actionable insights to help bridge technological divides and build a more ethical, equitable digital ecosystem for brain health.
Learning Objectives
At the conclusion of this session, attendees will be able to:
- Identify key opportunities and challenges associated with digital health technologies, artificial intelligence, and social media in advancing equitable brain health across diverse populations and healthcare settings.
- Apply practical strategies to evaluate, implement, and integrate digital health and AI-enabled tools into clinical and public health workflows while addressing barriers related to interoperability, privacy, clinician burden, and health equity.
- Discuss ethical, regulatory, and governance considerations for the responsible use of artificial intelligence and digital platforms in brain health, including approaches to mitigate bias, misinformation, and unintended disparities.
Speakers
- (Chair) Neha Dangayach, MD, MSCR, FAAN, FCCM, FNCS, FCCP, FANA
- (Speaker) Adys Mendizabal, MD, MS
- (Speaker) Baibing Chen, MD, MPH
- (Speaker) Amy Guzik, MD, FAHA, FAAN, FANA
Future of Digital Health and AI for Brain Health
Description
Artificial intelligence (AI) is rapidly transforming the field of neurology, offering new opportunities to enhance diagnosis, clinical decision-making, patient engagement, and healthcare delivery. As these technologies become increasingly integrated into clinical practice, it is essential to understand both their capabilities and their potential impact on health equity.
This presentation will provide a foundational overview of artificial intelligence and its current applications in digital health for brain health and neurological care. Participants will review core AI concepts, including machine learning, natural language processing, and large language models, and examine how these technologies are being incorporated into clinical workflows. Topics will also include current and emerging applications of AI in neurology, as well as the opportunities and challenges these tools present for reducing—or potentially exacerbating—healthcare disparities. Particular emphasis will be placed on the ethical, practical, and equity considerations that will shape the future of AI-enabled neurological care.
Attendees will leave with a shared understanding of the fundamental principles of AI, its evolving role in digital health, and the key opportunities and challenges that will influence the future of brain health and the responsible implementation of AI in neurology.
Brain Health and Youth
Description
Children and adolescents are developing within a rapidly changing digital environment shaped by social media, algorithmically curated content, and generative artificial intelligence. These technologies offer new opportunities for learning and connection while raising important questions about attention, sleep, cognition, and brain development. Understanding these changes is increasingly relevant to neurologists as today’s youth become tomorrow’s adult patients.
This presentation will examine current evidence on the relationship between digital technology and youth brain health, including research on attention, sleep, cognition, and emerging neurodevelopmental findings. Participants will also explore how generative AI is changing the way young people learn, seek information, and increasingly obtain health or emotional support. Throughout the presentation, established evidence will be distinguished from associations, plausible mechanisms, and long-term effects that remain unknown.
Attendees will leave with a practical framework for understanding how the digital environment may influence the developing brain, recognizing when technology use may be relevant to neurological symptoms, and considering how the next generation’s relationship with technology and AI may change the neurological history, patient-clinician interaction, and future practice of neurology.
The Great Digital Divide
Description
Digital health technologies are transforming the delivery of neurological care by expanding access to specialists, remote monitoring, and virtual care. However, disparities in technology access, digital literacy, broadband connectivity, and healthcare infrastructure continue to limit the benefits of these innovations for many patients and communities.
This presentation will explore how digital technologies are expanding access to neurological care while examining the challenges of bridging the digital divide to promote health equity. Participants will review current approaches to delivering technology-enabled neurological care in community settings, discuss barriers that contribute to disparities in access and adoption, and examine strategies to improve digital inclusion across diverse populations. Topics will also include opportunities to leverage telehealth, remote monitoring, mobile technologies, and other digital health tools to improve equitable access to high-quality neurological care.
Attendees will leave with a greater understanding of the factors contributing to the digital divide in neurology and practical insights into implementing digital health strategies that expand access, reduce disparities, and promote equitable neurological care for all patients.
Responsible AI in Neurology Patient Care: A Systematic Review of Clinical AI Algorithm (2020-2025)
Description
Artificial intelligence is increasingly studied in neurology for diagnosis, prognosis, screening, clinical scoring, and decision support. As these tools move closer to clinical workflows, clinicians need more than measures of technical performance to judge whether an AI system has been developed and evaluated in a way that supports clinically appropriate use. Responsible AI principles provide a framework for assessing clinical appropriateness, including the quality and provenance of data, validation and generalizability, potential bias, human oversight, safety, accountability, and clinical benefit. Clear reporting across these domains is therefore important for interpreting the evidence and assessing whether an AI application may be suitable for further clinical evaluation or implementation.
This presentation will review Responsible AI reporting in 1,055 neurological AI studies published between 2020 and 2026 across 12 domains. Although Data Quality and Provenance and Validation and Robustness were relatively well reported, overall Responsible AI reporting remained incomplete. Important deficiencies were identified in reporting related to Fairness, Equity and Bias, Monitoring and Lifecycle Management, Human Oversight and Workflow, and Safety and Clinical Benefit. Reporting improved only modestly across the study period. Differences were also observed among neurological subspecialties and between studies originating from high-income and low- and middle-income countries.
Attendees will leave with a practical framework for recognizing what information is often present, and what is frequently missing, when evaluating neurological AI studies. For neurologists and clinical researchers, these findings highlight questions to consider before interpreting or implementing an AI tool, including who was represented in the data, how the system was validated, how clinicians remain involved, and whether safety and patient-relevant benefit were adequately evaluated and reported. For researchers, developers, and reviewers, the findings identify opportunities to strengthen reporting so that future neurological AI research is easier to evaluate for transparency, equity, safety, clinical usefulness, and accountability.
