Modern views of machine learning for precision psychiatry
In light of the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC),
the advent of functional neuroimaging, novel technologies and methods provide new …
the advent of functional neuroimaging, novel technologies and methods provide new …
The synergy between deep learning and organs-on-chips for high-throughput drug screening: a review
Organs-on-chips (OoCs) are miniature microfluidic systems that have arguably become a
class of advanced in vitro models. Deep learning, as an emerging topic in machine learning …
class of advanced in vitro models. Deep learning, as an emerging topic in machine learning …
Off-policy evaluation for human feedback
Off-policy evaluation (OPE) is important for closing the gap between offline training and
evaluation of reinforcement learning (RL), by estimating performance and/or rank of target …
evaluation of reinforcement learning (RL), by estimating performance and/or rank of target …
Offline learning of closed-loop deep brain stimulation controllers for parkinson disease treatment
Q Gao, SL Schmidt, A Chowdhury, G Feng… - Proceedings of the …, 2023 - dl.acm.org
Deep brain stimulation (DBS) has shown great promise toward treating motor symptoms
caused by Parkinson's disease (PD), by delivering electrical pulses to the Basal Ganglia …
caused by Parkinson's disease (PD), by delivering electrical pulses to the Basal Ganglia …
Decision support for personalized therapy in implantable medical devices: A digital twin approach
H Yang, Z Jiang - Expert Systems with Applications, 2024 - Elsevier
Abstract Implantable Medical Devices (IMDs) offer timely therapeutic interventions for life-
threatening conditions without disrupting patients' daily activities. Given the substantial …
threatening conditions without disrupting patients' daily activities. Given the substantial …
Adaptive parameter modulation of deep brain stimulation based on improved supervisory algorithm
Y Zhu, J Wang, H Li, C Liu, WM Grill - Frontiers in neuroscience, 2021 - frontiersin.org
Clinically deployed deep brain stimulation (DBS) for the treatment of Parkinson's disease
operates in an open loop with fixed stimulation parameters, and this may result in high …
operates in an open loop with fixed stimulation parameters, and this may result in high …
Offline policy evaluation for learning-based deep brain stimulation controllers
Deep brain stimulation (DBS) is an effective procedure to treat motor symptoms caused by
nervous system disorders such as Parkinson's disease (PD). Although existing implantable …
nervous system disorders such as Parkinson's disease (PD). Although existing implantable …
{\epsilon}-Neural Thompson Sampling of Deep Brain Stimulation for Parkinson Disease Treatment
Deep Brain Stimulation (DBS) stands as an effective intervention for alleviating the motor
symptoms of Parkinson's disease (PD). Traditional commercial DBS devices are only able to …
symptoms of Parkinson's disease (PD). Traditional commercial DBS devices are only able to …
BGRL: Basal Ganglia inspired Reinforcement Learning based framework for deep brain stimulators
Abstract Deep Brain Stimulation (DBS) is an implantable medical device used for electrical
stimulation to treat neurological disorders. Traditional DBS devices provide fixed frequency …
stimulation to treat neurological disorders. Traditional DBS devices provide fixed frequency …
Robust exploration with adversary via Langevin Monte Carlo
In the realm of Deep Q-Networks (DQNs), numerous exploration strategies have
demonstrated efficacy within controlled environments. However, these methods encounter …
demonstrated efficacy within controlled environments. However, these methods encounter …