COVID-19 has caused many deaths worldwide. The automation of the diagnosis of this virus is highly desired. Convolutional neural networks (CNNs) have shown outstanding classification performance on image datasets. To date, it appears that COVID compu...
Deep reinforcement learning (DRL) augments the reinforcement learning framework, which learns a sequence of actions that maximizes the expected reward, with the representative power of deep neural networks. Recent works have demonstrated the great po...
COVID-19 has widely spread around the world, impacting the health systems of several countries in addition to the collateral damage that societies will face in the next years. Although the comparison between countries is essential for controlling thi...
Computational intelligence and neuroscience
Jul 27, 2021
Building energy efficiency is important because buildings consume a significant energy amount. The study proposed additive artificial neural networks (AANNs) for predicting energy use in residential buildings. A dataset in hourly resolution was used ...
The envisioned smart city domains are expected to rely heavily on artificial intelligence and machine learning (ML) approaches for their operations, where the basic ingredient is data. Privacy of the data and training time have been major roadblocks ...
Machine learning (ML) is a branch of artificial intelligence (AI) that enables computers to learn without being explicitly programmed, through a combination of statistics and computer science. It encompasses a variety of techniques used to analyse an...
International journal of environmental research and public health
Jul 22, 2021
The significant health and economic effects of COVID-19 emphasize the requirement for reliable forecasting models to avoid the sudden collapse of healthcare facilities with overloaded hospitals. Several forecasting models have been developed based on...
The accuracy of the prediction of stock price fluctuations is crucial for investors, and it helps investors manage funds better when formulating trading strategies. Using forecasting tools to get a predicted value that is closer to the actual value f...
Breast cancer is a heterogeneous disease. To guide proper treatment decisions for each patient, robust prognostic biomarkers, which allow reliable prognosis prediction, are necessary. Gene feature selection based on microarray data is an approach to ...
International journal of molecular sciences
Jul 19, 2021
Drug responses in cancer are diverse due to heterogenous genomic profiles. Drug responsiveness prediction is important in clinical response to specific cancer treatments. Recently, multi-class drug responsiveness models based on deep learning (DL) mo...