Coronavirus optimization algorithm: a bioinspired metaheuristic based on the COVID-19 propagation model
This study proposes a novel bioinspired metaheuristic simulating how the coronavirus
spreads and infects healthy people. From a primary infected individual (patient zero), the …
spreads and infects healthy people. From a primary infected individual (patient zero), the …
A comparison of instance-level counterfactual explanation algorithms for behavioral and textual data: SEDC, LIME-C and SHAP-C
Predictive systems based on high-dimensional behavioral and textual data have serious
comprehensibility and transparency issues: linear models require investigating thousands of …
comprehensibility and transparency issues: linear models require investigating thousands of …
Quantitative neurotoxicology: Potential role of artificial intelligence/deep learning approach
A Srivastava, JP Hanig - Journal of Applied Toxicology, 2021 - Wiley Online Library
Neurotoxicity studies are important in the preclinical stages of drug development process,
because exposure to certain compounds that may enter the brain across a permeable blood …
because exposure to certain compounds that may enter the brain across a permeable blood …
Can metafeatures help improve explanations of prediction models when using behavioral and textual data?
Abstract Machine learning models built on behavioral and textual data can result in highly
accurate prediction models, but are often very difficult to interpret. Linear models require …
accurate prediction models, but are often very difficult to interpret. Linear models require …
Gdaphen, R pipeline to identify the most important qualitative and quantitative predictor variables from phenotypic data
MM Muñiz Moreno, C Gavériaux-Ruff, Y Herault - BMC bioinformatics, 2023 - Springer
Background In individuals or animals suffering from genetic or acquired diseases, it is
important to identify which clinical or phenotypic variables can be used to discriminate …
important to identify which clinical or phenotypic variables can be used to discriminate …
[HTML][HTML] WebTraceSense—A Framework for the Visualization of User Log Interactions
The current surge in the deployment of web applications underscores the need to consider
users' individual preferences in order to enhance their experience. In response to this, an …
users' individual preferences in order to enhance their experience. In response to this, an …
Metafeatures-based rule-extraction for classifiers on behavioral and textual data
Machine learning models on behavioral and textual data can result in highly accurate
prediction models, but are often very difficult to interpret. Rule-extraction techniques have …
prediction models, but are often very difficult to interpret. Rule-extraction techniques have …
Computational efficient approximations of the concordance probability in a big data setting
Performance measurement is an essential task once a statistical model is created. The area
under the receiving operating characteristics curve (AUC) is the most popular measure for …
under the receiving operating characteristics curve (AUC) is the most popular measure for …
Protein function prediction using graph neural network with multi-type biological knowledge
Proteins play crucial roles in diverse biological functions, and accurately annotating their
functions is essential for understanding cellular mechanisms and developing therapies for …
functions is essential for understanding cellular mechanisms and developing therapies for …
Explaining prediction models to address ethical issues in business and society
S Goethals - 2024 - repository.uantwerpen.be
The field of artificial intelligence (AI) has experienced explosive growth in recent years, with
applications ranging from medical diagnosis to financial forecasting. However, as these …
applications ranging from medical diagnosis to financial forecasting. However, as these …