AIMC Topic: Neural Networks, Computer

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A Semi-supervised Deep Learning Method for Cervical Cell Classification.

Analytical cellular pathology (Amsterdam)
Currently, the Thinprep cytologic test (TCT) is the most popular cervical cancer cytology test technique. It can detect precancerous conditions and microbial infections. However, this technique entirely relies on manual operation and doctors' naked e...

Detection of Emotion of Speech for RAVDESS Audio Using Hybrid Convolution Neural Network.

Journal of healthcare engineering
Every human being has emotion for every item related to them. For every customer, their emotion can help the customer representative to understand their requirement. So, speech emotion recognition plays an important role in the interaction between hu...

A Liver Damage Prediction Using Partial Differential Segmentation with Improved Convolutional Neural Network.

Journal of healthcare engineering
BACKGROUND: The liver is one of the most significant and most essential organs in the human body. It is divided into two granular lobes, one on the right and one on the left, connected by a bile duct. The liver is essential in the removal of waste pr...

A Data-Efficient Framework for the Identification of Vaginitis Based on Deep Learning.

Journal of healthcare engineering
Vaginitis is a gynecological disease affecting the health of millions of women all over the world. The traditional diagnosis of vaginitis is based on manual microscopy, which is time-consuming and tedious. The deep learning method offers a fast and r...

5G Massive MIMO Signal Detection Algorithm Based on Deep Learning.

Computational intelligence and neuroscience
Aiming at the problems of poor signal detection effect caused by many interference factors in large-scale MIMO technology scene, this paper proposes a 5G massive MIMO signal detection algorithm based on deep learning. Firstly, the MIMO system model b...

Broad Echo State Network with Reservoir Pruning for Nonstationary Time Series Prediction.

Computational intelligence and neuroscience
The nonstationary time series is generated in various natural and man-made systems, of which the prediction is vital for advanced control and management. The neural networks have been explored in the time series prediction, but the problem remains in...

Multi-step wind speed forecasting based on a hybrid decomposition technique and an improved back-propagation neural network.

Environmental science and pollution research international
Accurate wind speed forecasting (WSF) not only ensures stable power system operation but also contributes to enhancing the competitiveness of wind power companies in the market. In this paper, a hybrid prediction model based on secondary decompositio...

A novel convolutional neural network for kidney ultrasound images segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Ultrasound imaging has been widely used in the screening of kidney diseases. The localization and segmentation of the kidneys in ultrasound images are helpful for the clinical diagnosis of diseases. However, it is a challeng...

Interpretable instance disease prediction based on causal feature selection and effect analysis.

BMC medical informatics and decision making
BACKGROUND: In the big wave of artificial intelligence sweeping the world, machine learning has made great achievements in healthcare in the past few years, however, these methods are only based on correlation, not causation. The particularities of t...

Application of Improved U-Net Convolutional Neural Network for Automatic Quantification of the Foveal Avascular Zone in Diabetic Macular Ischemia.

Journal of diabetes research
OBJECTIVES: The foveal avascular zone (FAZ) is a biomarker for quantifying diabetic macular ischemia (DMI), to automate the identification and quantification of the FAZ in DMI, using an improved U-Net convolutional neural network (CNN) and to establi...