#1 – Detecting Pre-Frailty and Frailty Using Free-Living Activity Monitoring from a Thigh-Worn Sensor
Andrew Song, Clinical Research Associate, Marcus Institute for Aging Research, Hebrew SeniorLife.
Andrew Song, Clinical Research Associate, Marcus Institute for Aging Research, Hebrew SeniorLife.
Zoom Registration: https://umass-amherst.zoom.us/meeting/register/VWDnTLPlTHGGmEtmUeE_7w#/registration Abstract: Artificial intelligence holds promise to transform care for older adults, yet today’s AI systems routinely underperform for this population due to poor data representation, limited validation, and weak alignment with lived experience. Drawing on a six-month collaboration between the SCAN Foundation, CHAI will be synthesizing evidence from literature review, expert interviews, and multi-stakeholder roundtables to surface why AI fails older adults—and what must change. They will outline practical pathways for building equitable AI, including multimodal data integration, standardized validation, local testing, and patient-centered deployment. The talk concludes with a roadmap for developing trustworthy AI that meaningfully improves outcomes for aging populations. Biography: Lucy Orr-Ewing, Head of Policy & Strategy, Coalition for Health AI (CHAI) Lucy Orr-Ewing leads Policy and Research for CHAI, where she leads policy engagement at both the state…
When: Friday, January 23rd, 2026Where: Mount Ida Campus of UMass Amherst in Newton, MA (In-person) | Zoom Webinar (Virtual option)Registration: Free Registration Link here MassAITC is hosting the Digital Frontiers in Frailty: Opportunities for Early Detection and Clinical Action Workshop. The free workshop will be held on January 23rd, 2026 at the Mount Ida Campus of UMass Amherst in Newton, MA and aims to bring together technologists (engineers, computer scientists, academic researchers, start-up founders) and clinicians (geriatricians, neurologists primary care providers) to redefine how we measure, assess, and provide time appropriate care for frailty. The workshop will include plenary speaker sessions from frailty and technology research experts, contributed poster and technology demo presentations, and a moderated discussion. By 2060, it is estimated that nearly a quarter of the US population (over 95 million people) will…
https://www.youtube.com/watch?v=XST7eqXmFQQ Abstract: Phishing attacks pose a significant threat to users, especially older adults. Existing defenses mainly focus on phishing detection but often cannot explain to lay users why a message is malicious. In this talk, I will discuss how we use Large Language Models (LLMs) to detect SMS phishing while generating evidence-based explanations. The key challenge is that SMS is short, lacking the necessary context for security reasoning. We develop a prototype called SmishX that gathers external contexts to augment the chain-of-thought (CoT) reasoning of LLMs and facilitate the explanation process. I will further discuss our user studies to evaluate the effectiveness and usability of SmishX. Finally, I will discuss the open challenges and opportunities of using AI to help older adults better protect themselves from cybersecurity threats in general. Biography: Gang Wang, PhD, Associate…
Professor of Computer Science, Manning CICS, UMass Amherst
Professor of Computer Science, Manning CICS, UMass Amherst