activity
20182023
most citedEvaluation of ChatGPT for NLP-based Mental Health Applications

58 citations · 68 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CL2023★ 58 cited

Evaluation of ChatGPT for NLP-based Mental Health Applications

Bishal Lamichhane

Large language models (LLM) have been successful in several natural language understanding tasks and could be relevant for natural language processing (NLP)-based mental health app…

cs.SD2022

Dyadic Interaction Assessment from Free-living Audio for Depression Severity Assessment

Bishal Lamichhane, Nidal Moukaddam, Ankit B. Patel +1

Psychomotor retardation in depression has been associated with speech timing changes from dyadic clinical interviews. In this work, we investigate speech timing features from free-…

cs.LG2022★ 2 cited

Psychotic Relapse Prediction in Schizophrenia Patients using A Mobile Sensing-based Supervised Deep Learning Model

Bishal Lamichhane, Joanne Zhou, Akane Sano

Mobile sensing-based modeling of behavioral changes could predict an oncoming psychotic relapse in schizophrenia patients for timely interventions. Deep learning models could compl…

cs.CY2022★ 8 cited

Improved Healthcare Access in Low-resource Regions: A Review of Technological Solutions

Bishal Lamichhane, Navaraj Neupane

Technological advancements have led to significant improvements in healthcare for prevention, diagnosis, treatments, and care. While resourceful regions can capitalize on state-of-…

eess.SP2021

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…

cs.LG2021

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…