Clinical evaluation of AI tools intended for older-adult care, including decision support, risk prediction, ambient documentation, and AI-assisted evidence synthesis. My work helps identify where technically promising systems may fail because of workflow mismatch, weak validation, unrealistic endpoints, or poor fit with complex older-adult populations.
Clinical evaluation of digital tools, caregiver platforms, remote monitoring systems, assistive devices, and aging-in-place technologies. My work focuses on whether products are usable for older adults, realistic for caregivers, compatible with clinical workflows, and meaningful in populations affected by frailty, cognitive impairment, sensory limitations, multimorbidity, and functional decline.
Assessment of whether studies, endpoints, eligibility criteria, and validation strategies reflect the realities of older patients: frailty, multimorbidity, cognitive impairment, polypharmacy, functional decline, and care dependence. Small design choices can determine whether a study becomes clinically useful or difficult to translate.
Interpretation of cognitive outcomes, blood-based biomarkers, and molecular signals in clinically complex older adults. I focus on whether biomarker strategies are not only scientifically interesting, but clinically meaningful, reproducible, and usable in real-world aging populations.
Clinical interpretation of medication burden, anticholinergic exposure, deprescribing opportunities, and drug-related functional or cognitive decline. This area is especially important when evaluating interventions, algorithms, or studies in populations where medication complexity can confound outcomes.
Evaluation of frailty, mobility, fall risk, functional status, and neuropsychiatric symptoms as clinically relevant outcomes in older adults. I focus on whether measurements capture what matters in practice: independence, vulnerability, recovery potential, and meaningful change over time.