Annals of agricultural and environmental medicine : AAEM
Jan 17, 2023
INTRODUCTION AND OBJECTIVE: Head and neck injuries are a heterogeneous group in terms of both clinical course and prognosis. For years, there have been attempts to create an ideal tool to predict the outcomes and severity of injuries. The aim of this...
A variety of new recurrent neural networks (RNNs) including the ODE-LSTM, Phased LSTM, CTGRU and GRU-D, were evaluated on modeling irregularly sampled PK/PD data with 6 or 12 time points/day and predicting PD data of unseen dosing regimens and dosing...
Neuroscientists have long characterized the properties and functions of the nervous system, and are increasingly succeeding in answering how brains perform the tasks they do. But the question 'why' brains work the way they do is asked less often. The...
BACKGROUND: The knee adduction moment, a biomechanical risk factor of knee osteoarthritis, is typically measured in a gait laboratory with expensive equipment and inverse dynamics modeling software. We aimed to develop a framework for a portable knee...
Current artificial intelligence systems for determining a person's emotions rely heavily on lip and mouth movement and other facial features such as eyebrows, eyes, and the forehead. Furthermore, low-light images are typically classified incorrectly ...
BACKGROUND: It is difficult for orthodontists to accurately predict the growth trend of the mandible in children with anterior crossbite. This study aims to develop a deep learning model to automatically predict the mandibular growth result into norm...
Neural network (NN) has been tentatively combined into multi-objective genetic algorithms (MOGAs) to solve the optimization problems in physics. However, the computationally complex physical evaluations and limited computing resources always cause th...
Biomedical physics & engineering express
Jan 17, 2023
This paper presents a method for estimating the x-ray energy spectrum for computed tomography (CT) in the diagnostic energy range from the reconstructed CT image itself. To this end, a virtual CT system was developed, and datasets, including CT image...
Computational intelligence and neuroscience
Jan 17, 2023
We proposed a novel deep convolutional neural network (DCNN) using inverted residuals and linear bottleneck layers for diagnosing grey blight disease on tea leaves. The proposed DCNN consists of three bottleneck blocks, two pairs of convolutional (Co...
The prediction of energy consumption is of great significance to the stability of the regional energy supply. In previous research on energy consumption forecasting, researchers have constantly proposed improved neural network prediction models or im...
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