Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Abstract: This paper presents LYRICEL, a framework integrating Knowledge Graph (KG) representation learning, Large Language Models (LLMs), and machine learning for reliable, explainable, and ...
Learn how to choose the right cross-validation method for your machine learning projects. Compare techniques like k-fold, stratified, and leave-one-out cross-validation, and understand when to use ...
Background and Purpose: Radiation dermatitis (RD), a common adverse reaction in breast cancer radiotherapy, impairs quality of life and increases healthcare burdens. Developing an effective risk ...
Objectives Alzheimer’s disease (AD) poses a significant challenge for individuals aged 65 and older, being the most prevalent form of dementia. Although existing AD risk prediction tools demonstrate ...
Abstract: Effective overtime planning in software projects remains a critical challenge due to the complex interplay between project constraints and human-centric decision-making. This study ...
If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...
1 Department of Computing Science, Faculty of Science, University of Alberta, Edmonton, AB, Canada 2 Computer Science Department, Faculty of Geology, University of Oviedo, Oviedo, Spain The ...
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