11 citations · 25 across the 7 of their papers we have counts for
7 papers
Remote Inference of Cognitive Scores in ALS Patients Using a Picture Description
Carla Agurto, Guillermo Cecchi, Bo Wen +4
Amyotrophic lateral sclerosis is a fatal disease that not only affects movement, speech, and breath but also cognition. Recent studies have focused on the use of language analysis…
Towards Healthy AI: Large Language Models Need Therapists Too
Baihan Lin, Djallel Bouneffouf, Guillermo Cecchi +1
Recent advances in large language models (LLMs) have led to the development of powerful AI chatbots capable of engaging in natural and human-like conversations. However, these chat…
Psychotherapy AI Companion with Reinforcement Learning Recommendations and Interpretable Policy Dynamics
Baihan Lin, Guillermo Cecchi, Djallel Bouneffouf
We introduce a Reinforcement Learning Psychotherapy AI Companion that generates topic recommendations for therapists based on patient responses. The system uses Deep Reinforcement…
Definition and clinical validation of Pain Patient States from high-dimensional mobile data: application to a chronic pain cohort
Jenna M. Reinen, Carla Agurto, Guillermo Cecchi +4
The technical capacity to monitor patients with a mobile device has drastically expanded, but data produced from this approach are often difficult to interpret. We present a soluti…
Working Alliance Transformer for Psychotherapy Dialogue Classification
Baihan Lin, Guillermo Cecchi, Djallel Bouneffouf
As a predictive measure of the treatment outcome in psychotherapy, the working alliance measures the agreement of the patient and the therapist in terms of their bond, task and goa…
PainPoints: A Framework for Language-based Detection of Chronic Pain and Expert-Collaborative Text-Summarization
Shreyas Fadnavis, Amit Dhurandhar, Raquel Norel +6
Chronic pain is a pervasive disorder which is often very disabling and is associated with comorbidities such as depression and anxiety. Neuropathic Pain (NP) is a common sub-type w…
SupervisorBot: NLP-Annotated Real-Time Recommendations of Psychotherapy Treatment Strategies with Deep Reinforcement Learning
Baihan Lin, Guillermo Cecchi, Djallel Bouneffouf
We propose a recommendation system that suggests treatment strategies to a therapist during the psychotherapy session in real-time. Our system uses a turn-level rating mechanism th…