Nikolaos Mylonas
YOU?
Author Swipe
View article: Automated Category and Trend Analysis of Scientific Articles on Ophthalmology Using Large Language Models: Development and Usability Study
Automated Category and Trend Analysis of Scientific Articles on Ophthalmology Using Large Language Models: Development and Usability Study Open
Background In this paper, we present an automated method for article classification, leveraging the power of large language models (LLMs). Objective The aim of this study is to evaluate the applicability of various LLMs based on textual co…
View article: Automated Category and Trend Analysis of Scientific Articles on Ophthalmology Using Large Language Models: Development and Usability Study (Preprint)
Automated Category and Trend Analysis of Scientific Articles on Ophthalmology Using Large Language Models: Development and Usability Study (Preprint) Open
BACKGROUND In this paper, we present an automated method for article classification, leveraging the power of large language models (LLMs). OBJECTIVE The aim of this study is to evaluate the applicability of various LLMs based on textual…
View article: Local Interpretability of Random Forests for Multi-Target Regression
Local Interpretability of Random Forests for Multi-Target Regression Open
Multi-target regression is useful in a plethora of applications. Although random forest models perform well in these tasks, they are often difficult to interpret. Interpretability is crucial in machine learning, especially when it can dire…
View article: On the Persistence of Multilabel Learning, Its Recent Trends, and Its Open Issues
On the Persistence of Multilabel Learning, Its Recent Trends, and Its Open Issues Open
Multilabel data comprise instances associated with multiple binary target variables. The main learning task from such data is multilabel classification, where the goal is to output a bipartition of the target variables into relevant and ir…
View article: WeakMeSH: Leveraging provenance information for weakly supervised classification of biomedical articles with emerging MeSH descriptors
WeakMeSH: Leveraging provenance information for weakly supervised classification of biomedical articles with emerging MeSH descriptors Open
Medical Subject Headings (MeSH) is a hierarchically structured thesaurus created by the National Library of Medicine of USA. Each year the vocabulary gets revised, bringing forth different types of changes. Those of particular interest are…
View article: An Attention Matrix for Every Decision: Faithfulness-based Arbitration Among Multiple Attention-Based Interpretations of Transformers in Text Classification
An Attention Matrix for Every Decision: Faithfulness-based Arbitration Among Multiple Attention-Based Interpretations of Transformers in Text Classification Open
Transformers are widely used in natural language processing, where they consistently achieve state-of-the-art performance. This is mainly due to their attention-based architecture, which allows them to model rich linguistic relations betwe…
View article: Local Multi-Label Explanations for Random Forest
Local Multi-Label Explanations for Random Forest Open
Multi-label classification is a challenging task, particularly in domains where the number of labels to be predicted is large. Deep neural networks are often effective at multi-label classification of images and textual data. When dealing …
View article: Monitoring of free-range rabbits using aerial thermal imaging
Monitoring of free-range rabbits using aerial thermal imaging Open
View article: The Future of Digital Agriculture: Technologies and Opportunities
The Future of Digital Agriculture: Technologies and Opportunities Open
This article presents key technological advances in the digital agriculture, which will have significant impact. Artificial intelligence-based techniques, together with big data analytics, address the challenges of agricultural production …