36 citations · 62 across the 5 of their papers we have counts for
5 papers
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…
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…
Modern Views of Machine Learning for Precision Psychiatry
Zhe Sage Chen, Prathamesh, Kulkarni +4
In light of the NIMH's Research Domain Criteria (RDoC), the advent of functional neuroimaging, novel technologies and methods provide new opportunities to develop precise and perso…
Prediction of clinical tremor severity using Rank Consistent Ordinal Regression
Li Zhang, Vijay Yadav, Vidya Koesmahargyo +2
Tremor is a key diagnostic feature of Parkinson's Disease (PD), Essential Tremor (ET), and other central nervous system (CNS) disorders. Clinicians or trained raters assess tremor…
Direct Classification of Emotional Intensity
Jacob Ouyang, Isaac R Galatzer-Levy, Vidya Koesmahargyo +1
In this paper, we present a model that can directly predict emotion intensity score from video inputs, instead of deriving from action units. Using a 3d DNN incorporated with dynam…