AIMC Topic: Neural Networks, Computer

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A Computer-Aided Diagnosis System Using Deep Learning for Multiclass Skin Lesion Classification.

Computational intelligence and neuroscience
In the USA, each year, almost 5.4 million people are diagnosed with skin cancer. Melanoma is one of the most dangerous types of skin cancer, and its survival rate is 5%. The development of skin cancer has risen over the last couple of years. Early id...

CNN-GRU-AM for Shared Bicycles Demand Forecasting.

Computational intelligence and neuroscience
The demand forecast of shared bicycles directly determines the utilization rate of vehicles and projects operation benefits. Accurate prediction based on the existing operating data can reduce unnecessary delivery. Since the use of shared bicycles is...

Deep reconstruction-recoding network for unsupervised domain adaptation and multi-center generalization in colonoscopy polyp detection.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Currently, the best performing methods in colonoscopy polyp detection are primarily based on deep neural networks (DNNs), which are usually trained on large amounts of labeled data. However, different hospitals use different...

What makes a good prediction? Feature importance and beginning to open the black box of machine learning in genetics.

Human genetics
Genetic data have become increasingly complex within the past decade, leading researchers to pursue increasingly complex questions, such as those involving epistatic interactions and protein prediction. Traditional methods are ill-suited to answer th...

A contextual multi-task neural approach to medication and adverse events identification from clinical text.

Journal of biomedical informatics
Effective wide-scale pharmacovigilance calls for accurate named entity recognition (NER) of medication entities such as drugs, dosages, reasons, and adverse drug events (ADE) from clinical text. The scarcity of adverse event annotations and underlyin...

Noise Eliminated Ensemble Empirical Mode Decomposition Scalogram Analysis for Rotating Machinery Fault Diagnosis.

Sensors (Basel, Switzerland)
Rotating machinery is one of the major components of industries that suffer from various faults due to the constant workload. Therefore, a fast and reliable fault diagnosis method is essential for machine condition monitoring. In this study, noise el...

CFNet: LiDAR-Camera Registration Using Calibration Flow Network.

Sensors (Basel, Switzerland)
As an essential procedure of data fusion, LiDAR-camera calibration is critical for autonomous vehicles and robot navigation. Most calibration methods require laborious manual work, complicated environmental settings, and specific calibration targets....

Automatic Evaluation of Histological Prognostic Factors Using Two Consecutive Convolutional Neural Networks on Kidney Samples.

Clinical journal of the American Society of Nephrology : CJASN
BACKGROUND AND OBJECTIVES: The prognosis of patients undergoing kidney tumor resection or kidney donation is linked to many histologic criteria. These criteria notably include glomerular density, glomerular volume, vascular luminal stenosis, and seve...

BreaCNet: A high-accuracy breast thermogram classifier based on mobile convolutional neural network.

Mathematical biosciences and engineering : MBE
The presence of a well-trained, mobile CNN model with a high accuracy rate is imperative to build a mobile-based early breast cancer detector. In this study, we propose a mobile neural network model breast cancer mobile network (BreaCNet) and its imp...

Energy Consumption Forecasting for Smart Meters Using Extreme Learning Machine Ensemble.

Sensors (Basel, Switzerland)
The employment of smart meters for energy consumption monitoring is essential for planning and management of power generation systems. In this context, forecasting energy consumption is a valuable asset for decision making, since it can improve the p...