LymeDot: Using Open Data and Mobile AI for Symptom Tracking in Lyme Disease
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I presented work at the White House Open Data Innovation Summit in Washington, D.C., where our team was invited to present our project developed during a Boston-based health hackathon. Our project, LymeDot, explored how mobile technology and open data could help patients with Lyme disease track symptoms over time, support clinical decision-making, and empower individuals managing complex, chronic conditions.
Lyme disease patients frequently report fluctuating, nonspecific symptoms and unpredictable relapses, while clinicians struggle to interpret fragmented histories and evaluate treatment response. LymeDot aimed to bridge this gap by enabling patients to record daily symptoms, triggers, and treatments through an easy-to-use phone app. We proposed applying AI to identify personalized patterns, such as factors associated with symptom exacerbations, and to surface insights that could be shared securely with clinicians.
At the Summit, we discussed how open data ecosystems and patient-generated health data could improve understanding of chronic illnesses like Lyme disease, and how mobile tools can reduce the documentation burden on patients who often experience fatigue and cognitive impairment. The presentation was part of a broader national conversation about using open data, AI, and user-centered design to advance health, wellness, and patient empowerment.
