In plain words: A language model is taught to read raw sensor numbers—heart signals, steps, movement—by tuning it on just a handful of health examples. It then handles tasks like spotting heart trouble, recognizing activity, estimating calories, and scoring stress, which text-only models cannot.
Abstract · Large Language Models are Few-Shot Health Learners
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 text-based inferences, health applications require that models be grounded in numerical data (e.g., vital signs, laboratory values in clinical domains; steps, movement in the wellness domain) that is not easily or readily expressed as text in existing training corpus. We demonstrate that with only few-shot tuning, a large language model is capable of grounding various physiological and behavioral time-series data and making meaningful inferences on numerous health tasks for both clinical and wellness contexts. Using data from wearable and medical sensor recordings, we evaluate these capabilities on the tasks of cardiac signal analysis, physical activity recognition, metabolic calculation (e.g., calories burned), and estimation of stress reports and mental health screeners.
Xin Liu, Daniel McDuff, Geza Kovacs, Isaac Galatzer-Levy, Jacob Sunshine, Jiening Zhan, Ming-Zher Poh, Shun Liao, Paolo Di Achille, Shwetak Patel
arXiv:2305.15525 · cs.CL, cs.LG · submitted May 24, 2023
abstract · pdf · html
On the one hand, there are SO many reasons using LLMs to help people make health decisions should be an utterly terrible idea, to the point of immorality:
- They hallucinate
- They can't do mathematical calculations
- They're incredibly good at being convincing, no matter what junk they are outputting
And yet, despite being very aware of these limitations, I've already found myself using them for medical advice (for pets so far, not yet for humans). And the advice I got seemed useful, and helped kick off additional research and useful conversations with veterinary staff.
Plenty of people have very limited access to useful medical advice.
There are plenty of medical topics which people find embarrassing, and would prefer to - at least initially - talk to a chatbot than to their own doctor.
Do the benefits outweight the risks? As with pretty much every ethical question involving LLMs, there are no obviously correct answers here.