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Analyzing the Impact of Oncological Data at Different Time Points and Tumor Biomarkers on Artificial Intelligence Predictions for Five-Year Survival in Esophageal Cancer
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Impact of Nature of Medical Data on Machine and Deep Learning for Imbalanced Datasets: Clinical Validity of SMOTE Is Questionable
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Why Do Tree Ensemble Approximators Not Outperform the Recursive-Rule eXtraction Algorithm?
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Augmenting Deep Neural Networks with Symbolic Educational Knowledge: Towards Trustworthy and Interpretable AI for Education
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Representing Human Ethical Requirements in Hybrid Machine Learning Models: Technical Opportunities and Fundamental Challenge
Journal Description
Machine Learning and Knowledge Extraction
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), dblp, and other databases.
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 27.1 days after submission; acceptance to publication is undertaken in 4.6 days (median values for papers published in this journal in the first half of 2024).
- Journal Rank: JCR - Q2 (Computer Science, Artificial Intelligence) / CiteScore - Q1 (Engineering (miscellaneous))
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
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