International journal of computer assisted radiology and surgery
Sep 20, 2024
PURPOSE: The search for heart components in robotic transthoracic echocardiography is a time-consuming process. This paper proposes an optimized robotic navigation system for heart components using deep reinforcement learning to achieve an efficient ...
Neural networks : the official journal of the International Neural Network Society
Sep 20, 2024
Approximating nonlinear differential equations using a neural network provides a robust and efficient tool for various scientific computing tasks, including real-time predictions, inverse problems, optimal controls, and surrogate modeling. Previous w...
Computer methods and programs in biomedicine
Sep 20, 2024
BACKGROUND AND OBJECTIVE: Computational models of hemodynamics can contribute to optimizing surgical plans, and improve our understanding of cardiovascular diseases. Recently, machine learning methods have become essential to reduce the computational...
Neural networks : the official journal of the International Neural Network Society
Sep 20, 2024
This study examines the fixed-time synchronization (FXTS) problem of delayed multiple inertial neural networks (MINNs) against cyber-physical attacks (CPA) execute an uncertain impulse, using reaction-diffusion (RD) terms. Using fixed-time stability ...
Neural networks : the official journal of the International Neural Network Society
Sep 20, 2024
State representations considerably accelerate learning speed and improve data efficiency for deep reinforcement learning (DRL), especially for visual tasks. Task-relevant state representations could focus on features relevant to the task, filter out ...
American journal of preventive medicine
Sep 20, 2024
INTRODUCTION: Starting June 30, 2022, Google implemented its revised Inappropriate Content Advertising Policy, targeting discriminatory skin-lightening ads that suggest superiority of certain skin shades. This study evaluates the ad content changes f...
OBJECTIVE: Approximately 30 % of thyroid nodules yield an indeterminate diagnosis through conventional diagnostic strategies. The aim of this study was to develop machine learning (ML) models capable of identifying papillary thyroid carcinomas using ...
Journal of medical radiation sciences
Sep 20, 2024
In a stretched healthcare system, radiographer preliminary image evaluation in the acute setting can be a means to optimise patient care by reducing error and increasing efficiencies in the patient journey. Radiographers have shown impressive accurac...
BACKGROUND: Perfusion magnetic resonance imaging (MRI)s plays a central role in the diagnosis and monitoring of neurovascular or neurooncological disease. However, conventional processing techniques are limited in their ability to capture relevant ch...
Numerous automatic sleep stage classification systems have been developed, but none have become effective assistive tools for sleep technicians due to issues with generalization. Four key factors hinder the generalization of these models are instrume...
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