Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...

Abstract: A problem with machine learning (ML) techniques for detecting intrusions in the Internet of Things (IoT) is that they are ineffective in the detection of low-frequency intrusions. In ...

A Support Vector Machine (SVM) is a supervised machine learning model. In its basic form SVMs are used for binary classification tasks. Their fundamental idea is to learn a hyperplane which separates ...

Abstract: Building collapses, irrespective of structure type or location, result in global tragedies. Rapid rescue efforts are essential, especially within the critical three-day window for trapped ...

1 Department of Computer Science, Chennai Mathematical Institute, Chennai, India. 2 Department of Mathematics & Computer Science, Chennai Mathematical Institute, Chennai, India. 3 Department of Data ...

The full paper may be read at arXiv.org. For instance, use the CNN-SVM model. $ cd malware-classification $ python3 main.py --model 1 --dataset ./dataset/malimg.npz --num_epochs 100 ...

Objective: We aimed to develop machine learning (ML)–based models to predict the risk of PR in older adults. Methods: This study conducted a cross-sectional secondary data analysis based on 1026 older ...

Genomic prediction (GP) has revolutionized animal and plant breeding. However, better statistical models that can improve the accuracy of GP are required. For this reason, in this study, we explored ...

Polystyrene binding peptides (PSBPs) play a key role in the immobilization process. The correct identification of PSBPs is the first step of all related works. In this paper, we proposed a novel ...