32 citations · 100 across the 7 of their papers we have counts for
7 papers
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…
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…
Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL
Baihan Lin, Guillermo Cecchi, Djallel Bouneffouf +2
Artificial behavioral agents are often evaluated based on their consistent behaviors and performance to take sequential actions in an environment to maximize some notion of cumulat…
Thou Shalt Not Reject the P-value
Oliver Y. Chén, Raúl G. Saraiva, Guy Nagels +9
Since its debut in the 18th century, the P-value has been an important part of hypothesis testing-based scientific discoveries. As the statistical engine accelerates, questions are…
A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry
Baihan Lin, Guillermo Cecchi, Djallel Bouneffouf +2
Drawing an inspiration from behavioral studies of human decision making, we propose here a more general and flexible parametric framework for reinforcement learning that extends st…
Ariadne: Analysis for Machine Learning Program
Julian Dolby, Avraham Shinnar, Allison Allain +1
Machine learning has transformed domains like vision and translation, and is now increasingly used in science, where the correctness of such code is vital. Python is popular for ma…
Autism Classification Using Brain Functional Connectivity Dynamics and Machine Learning
Ravi Tejwani, Adam Liska, Hongyuan You +2
The goal of the present study is to identify autism using machine learning techniques and resting-state brain imaging data, leveraging the temporal variability of the functional co…