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Found 7 papers, 1 papers with code
GPT-4's assessment of its performance in a USMLE-based case study
This study investigates GPT-4's assessment of its performance in healthcare applications.
The Confidence-Competence Gap in Large Language Models: A Cognitive Study
We exploit these models with diverse sets of questionnaires and real-world scenarios and extract how LLMs exhibit confidence in their responses.
Evaluation of ChatGPT for NLP-based Mental Health Applications
In this work, we report the performance of LLM-based ChatGPT (with gpt-3. 5-turbo backend) in three text-based mental health classification tasks: stress detection (2-class classification), depression detection (2-class classification), and suicidality detection (5-class classification).
Dyadic Interaction Assessment from Free-living Audio for Depression Severity Assessment
Psychomotor retardation in depression has been associated with speech timing changes from dyadic clinical interviews.
Psychotic Relapse Prediction in Schizophrenia Patients using A Mobile Sensing-based Supervised Deep Learning Model
The CrossCheck dataset consisting of continuous mobile sensing data obtained from 63 schizophrenia patients, each monitored for up to a year, was used for our evaluations.
Patient-independent Schizophrenia Relapse Prediction Using Mobile Sensor based Daily Behavioral Rhythm Changes
In this work, we investigated a machine learning based schizophrenia relapse prediction model using mobile sensing data to characterize behavioral features.
Routine Clustering of Mobile Sensor Data Facilitates Psychotic Relapse Prediction in Schizophrenia Patients
The clustering model based features, together with other features characterizing the mobile sensing data, resulted in an F2 score of 0. 24 for the relapse prediction task in a leave-one-patient-out evaluation setting.
