34 citations · 35 across the 5 of their papers we have counts for
5 papers
Automated Detection and Classification of Delusion-related Content in Naturalistic Audio Diaries Using Multi-Agent Language Models
Feng Chen, Justin Tauscher, Changye Li +7
Speech monologues recorded in naturalistic settings provide opportunities to characterize mental illness phenomenology and detect symptom exacerbation. Large language models (LLMs)…
Detecting PTSD in Clinical Interviews: A Comparative Analysis of NLP Methods and Large Language Models
Feng Chen, Dror Ben-Zeev, Gillian Sparks +2
Post-Traumatic Stress Disorder (PTSD) remains underdiagnosed in clinical settings, presenting opportunities for automated detection to identify patients. This study evaluates natur…
Bigger But Not Better: Small Neural Language Models Outperform Large Language Models in Detection of Thought Disorder
Changye Li, Weizhe Xu, Serguei Pakhomov +3
Disorganized thinking is a key diagnostic indicator of schizophrenia-spectrum disorders. Recently, clinical estimates of the severity of disorganized thinking have been shown to co…
Patient-independent Schizophrenia Relapse Prediction Using Mobile Sensor based Daily Behavioral Rhythm Changes
Bishal Lamichhane, Dror Ben-Zeev, Andrew Campbell +9
A schizophrenia relapse has severe consequences for a patient's health, work, and sometimes even life safety. If an oncoming relapse can be predicted on time, for example by detect…
Routine Clustering of Mobile Sensor Data Facilitates Psychotic Relapse Prediction in Schizophrenia Patients
Joanne Zhou, Bishal Lamichhane, Dror Ben-Zeev +2
We aim to develop clustering models to obtain behavioral representations from continuous multimodal mobile sensing data towards relapse prediction tasks. The identified clusters co…