Results 61 to 70 of about 544,487 (316)

Methods for working with problem residents in medical physics residency education

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Medical physics residency training programs may occasionally encounter residents requiring additional intervention beyond normal training efforts. In the literature, these residents are referred to as “problem” residents. While the physician literature on the subject is valuable, this paper specifically focuses on dealing with a problem ...
Christopher J. Watchman, Dandan Zheng
wiley   +1 more source

Reinforcement learning-based link adaptation in long delayed underwater acoustic channel [PDF]

MATEC Web of Conferences, 2019
In this paper, we apply reinforcement learning, a significant area of machine learning, to formulate an optimal self-learning strategy to interact in an unknown and dynamically variable underwater channel.
Wang Jingxi, Yuen Chau, Guan Yong Liang, Ge Fengxiang   +3 more
doaj   +1 more source

Transfer Learning in Deep Reinforcement Learning: A Survey [PDF]

arXiv, 2020
Reinforcement learning is a learning paradigm for solving sequential decision-making problems. Recent years have witnessed remarkable progress in reinforcement learning upon the fast development of deep neural networks. Along with the promising prospects of reinforcement learning in numerous domains such as robotics and game-playing, transfer learning ...
arxiv  

Accelerate Reinforcement Learning with PID Controllers in the Pendulum Simulations [PDF]

arXiv, 2022
We propose a Proportional Integral Derivative (PID) controller-based coaching scheme to expedite reinforcement learning (RL).
arxiv  

Amygdala Neurodegeneration: A Key Driver of Visual Dysfunction in Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Visual disability in Parkinson's disease (PD) is not fully explained by retinal neurodegeneration. We aimed to delineate the brain substrate of visual dysfunction in PD and its association with retinal thickness. Methods Forty‐two PD patients and 29 controls underwent 3‐Tesla MRI, retinal spectral‐domain optical coherence tomography,
Asier Erramuzpe, Ane Murueta‐Goyena, Antonio Jimenez‐Marin, Marian Acera, Sara Teijeira‐Portas, Rocío Del Pino, Tamara Fernández‐Valle, Ibai Diez, Unai Sainz‐Lugarezaresti, Naroa Ibarretxe‐Bilbao, Unai Ayala, Maitane Barrenechea, Alberto Cabrera‐Zubizarreta, Jesús Cortés, Juan Carlos Gómez‐Esteban, Iñigo Gabilondo   +15 more
wiley   +1 more source

Breakthrough Solution for Antimicrobial Resistance Detection: Surface‐Enhanced Raman Spectroscopy‐based on Artificial Intelligence

Advanced Materials Interfaces, EarlyView., 2023
This review discusses the use of Surface‐Enhanced Raman Spectroscopy (SERS) combined with Artificial Intelligence (AI) for detecting antimicrobial resistance (AMR). Various SERS studies used with AI techniques, including machine learning and deep learning, are analyzed for their advantages and limitations.
Zakarya Al‐Shaebi, Munevver Akdeniz, Awel Olsido Ahmed, Mine Altunbek, Omer Aydin   +4 more
wiley   +1 more source

Home‐Based Tele‐tDCS in Amyotrophic Lateral Sclerosis: Feasibility, Safety, and Preliminary Efficacy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with limited treatment options. Transcranial direct current stimulation (tDCS) shows promise as a neuromodulatory intervention in various neurological disorders, but its application in ALS, particularly in a remote, home‐based format, remains underexplored.
Sangeetha Madhavan, Shravni Deshmukh, Mark Cummings, Aditi Doshi, Kourosh Rezania, Sally Freels, Gina Sawa   +6 more
wiley   +1 more source

Deep Forest Reinforcement Learning for Preventive Strategy Considering Automatic Generation Control in Large-Scale Interconnected Power Systems

Applied Sciences, 2018
To reduce occurrences of emergency situations in large-scale interconnected power systems with large continuous disturbances, a preventive strategy for the automatic generation control (AGC) of power systems is proposed.
Linfei Yin, Lulin Zhao, Tao Yu, Xiaoshun Zhang   +3 more
doaj   +1 more source

Using Inverse Reinforcement Learning with Real Trajectories to Get More Trustworthy Pedestrian Simulations

Mathematics, 2020
Reinforcement learning is one of the most promising machine learning techniques to get intelligent behaviors for embodied agents in simulations. The output of the classic Temporal Difference family of Reinforcement Learning algorithms adopts the form of ...
Francisco Martinez-Gil, Miguel Lozano, Ignacio García-Fernández, Pau Romero, Dolors Serra, Rafael Sebastián   +5 more
doaj   +1 more source

Barriers and Facilitators for Implementing Resilience Coaching for Youth With Chronic Musculoskeletal Pain: Pediatric Rheumatologists’ Perspectives

Arthritis Care &Research, EarlyView.
Objective Promoting Resilience in Stress Management (PRISM) is a resilience coaching program designed for adolescents with chronic illness. We aimed to examine the perceived feasibility, acceptability, and appropriateness of PRISM among pediatric rheumatologists treating adolescents with chronic musculoskeletal pain and obtain recommendations for ...
Sabrina Gmuca, Anyun Chatterjee, Mackenzie McGill, Nellie Butler, Katherine S. Kellom, Jami F. Young, Tonya M. Palermo, Pamela F. Weiss, Abby R. Rosenberg, Peter F. Cronholm   +9 more
wiley   +1 more source