Extracting time-varying latent variables from computational cognitive models plays a key role in uncovering the dynamic cognitive processes that drive behaviors. However, existing methods are limited to inferring latent variable sequences in a relati...
Survival analysis plays a crucial aspect in medical research and other domains where understanding the time-to-events is paramount. In this study, we present a novel approach for estimating survival outcomes that combines Bayesian neural networks wit...
We present a novel computational framework that combines Agent-Based Modeling (ABM) with Reinforcement Learning (RL) using the Double Deep Q-Network (DDQN) algorithm to determine cellular behavior in response to environmental signals. With this appro...
BACKGROUND: Staphylococcus aureus and Staphylococcus epidermidis are tenacious pathogens that cause toxic shock syndrome. Accessory gene regulator (Agr) of Staphylococcus sp. controls the expression of multiple genes that encode virulence properties....
This research investigates the impact of bacterial growth on the pH of culture media, emphasizing its significance in microbiological and biotechnological applications. A range of sophisticated artificial intelligence methods, including One-Dimension...
Humans use diverse skills and strategies to effectively manipulate various objects, ranging from dexterous in-hand manipulation (fine motor skills) to complex whole-body manipulation (gross motor skills). The latter involves full-body engagement and ...
Neuromorphic computing has got more attention in various tasks during recent years. The main goal of this field is to explore neural functionality in the brain. The studies of spiking neurons and Spiking Neural Networks (SNNs) are vital to understand...
The integration of AI simulation models within smart electrical prosthetic systems represents a significant advancement in disability disease diagnosis. However, the selection and evaluation of these AI models interpret some multi-criteria decision-m...
The amygdala plays a central role in emotion, memory, and decision-making and comprises approximately 13 distinct nuclei with connectivity. Despite its functional importance, high-resolution subnuclear mapping is challenging. This study aimed to cons...
Conventional approaches to material decomposition in spectral CT face challenges related to precise algorithm calibration across imaged conditions and low signal quality caused by variable object size and reduced dose. In this proof-of-principle stud...
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