AIMC Topic: Machine Learning

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Hyper-flexible Convolutional Neural Networks based on Generalized Lehmer and Power Means.

Neural networks : the official journal of the International Neural Network Society
Convolutional Neural Network is one of the famous members of the deep learning family of neural network architectures, which is used for many purposes, including image classification. In spite of the wide adoption, such networks are known to be highl...

The requirements for performing artificial-intelligence-related research and model development.

Pediatric radiology
Artificial intelligence research in health care has undergone tremendous growth in the last several years thanks to the explosion of digital health care data and systems that can leverage large amounts of data to learn patterns that can be applied to...

Explainability and Transparency of Classifiers for Air-Handling Unit Faults Using Explainable Artificial Intelligence (XAI).

Sensors (Basel, Switzerland)
In recent years, explainable artificial intelligence (XAI) techniques have been developed to improve the explainability, trust and transparency of machine learning models. This work presents a method that explains the outputs of an air-handling unit ...

LTPConstraint: a transfer learning based end-to-end method for RNA secondary structure prediction.

BMC bioinformatics
BACKGROUND: RNA secondary structure is very important for deciphering cell's activity and disease occurrence. The first method which was used by the academics to predict this structure is biological experiment, But this method is too expensive, causi...

mRNAsi-related metabolic risk score model identifies poor prognosis, immunoevasive contexture, and low chemotherapy response in colorectal cancer patients through machine learning.

Frontiers in immunology
Colorectal cancer (CRC) is one of the most fatal cancers of the digestive system. Although cancer stem cells and metabolic reprogramming have an important effect on tumor progression and drug resistance, their combined effect on CRC prognosis remains...

Separation of Different Blogs from Skin Disease Data using Artificial Intelligence.

Computational intelligence and neuroscience
A combination of environmental conditions may cause skin illness everywhere on the earth, and it is one of the most dangerous diseases that can develop as a result. A major goal in the selection of characteristics is to produce predictions about skin...

Research on a Machine Learning-Based Method for Assessing the Safety State of Historic Buildings.

Computational intelligence and neuroscience
Historic and protected buildings are increasingly valued due to their valuable historical and cultural value. The assessment of the safety state of historic buildings has received more attention. Emerging machine learning algorithms, with their excel...

Aerial Separation and Receiver Arrangements on Identifying Lung Syndromes Using the Artificial Neural Network.

Computational intelligence and neuroscience
Lung disease is one of the most harmful diseases in traditional days and is the same nowadays. Early detection is one of the most crucial ways to prevent a human from developing these types of diseases. Many researchers are involved in finding variou...

Aging Time Prediction Model Analysis and Numerical Simulation of Random Degradation Equipment Based on Big Data Linkage Technology.

Computational intelligence and neuroscience
In this study, we focus on the relevance of remaining life prediction of randomly degraded equipment in the context of big data monitoring and the core issue of quantifying uncertainty in remaining life prediction. We analyze the limitations and comm...

Text-Based Emotion Recognition Using Deep Learning Approach.

Computational intelligence and neuroscience
Sentiment analysis is a method to identify people's attitudes, sentiments, and emotions towards a given goal, such as people, activities, organizations, services, subjects, and products. Emotion detection is a subset of sentiment analysis as it predi...