77 citations · 261 across the 24 of their papers we have counts for
9 papers · 1 filter
The Capability of Large Language Models to Measure Psychiatric Functioning
Isaac R. Galatzer-Levy, Daniel McDuff, Vivek Natarajan +2
The current work investigates the capability of Large language models (LLMs) that are explicitly trained on large corpuses of medical knowledge (Med-PaLM 2) to predict psychiatric…
Research Protocol for the Google Health Digital Well-being Study
Daniel McDuff, Andrew Barakat, Ari Winbush +6
The impact of digital device use on health and well-being is a pressing question to which individuals, families, schools, policy makers, legislators, and digital designers are all…
Large Language Models are Few-Shot Health Learners
Xin Liu, Daniel McDuff, Geza Kovacs +7
Large language models (LLMs) can capture rich representations of concepts that are useful for real-world tasks. However, language alone is limited. While existing LLMs excel at tex…
"Can't Take the Pressure?": Examining the Challenges of Blood Pressure Estimation via Pulse Wave Analysis
Suril Mehta, Nipun Kwatra, Mohit Jain +1
The use of observed wearable sensor data (e.g., photoplethysmograms [PPG]) to infer health measures (e.g., glucose level or blood pressure) is a very active area of research. Such…
A Review of Deep Learning for Video Captioning
Moloud Abdar, Meenakshi Kollati, Swaraja Kuraparthi +8
Video captioning (VC) is a fast-moving, cross-disciplinary area of research that bridges work in the fields of computer vision, natural language processing (NLP), linguistics, and…
Synthetic Data in Healthcare
Daniel McDuff, Theodore Curran, Achuta Kadambi
Synthetic data are becoming a critical tool for building artificially intelligent systems. Simulators provide a way of generating data systematically and at scale. These data can t…