122 citations · 171 across the 8 of their papers we have counts for
6 papers · 1 filter
A global analysis of metrics used for measuring performance in natural language processing
Kathrin Blagec, Georg Dorffner, Milad Moradi +2
Measuring the performance of natural language processing models is challenging. Traditionally used metrics, such as BLEU and ROUGE, originally devised for machine translation and s…
Deep learning models are not robust against noise in clinical text
Milad Moradi, Kathrin Blagec, Matthias Samwald
Artificial Intelligence (AI) systems are attracting increasing interest in the medical domain due to their ability to learn complicated tasks that require human intelligence and ex…
Evaluating the Robustness of Neural Language Models to Input Perturbations
Milad Moradi, Matthias Samwald
High-performance neural language models have obtained state-of-the-art results on a wide range of Natural Language Processing (NLP) tasks. However, results for common benchmark dat…
Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts
Milad Moradi, Matthias Samwald
In recent years, summarizers that incorporate domain knowledge into the process of text summarization have outperformed generic methods, especially for summarization of biomedical…
Text Summarization in the Biomedical Domain
Milad Moradi, Nasser Ghadiri
This chapter gives an overview of recent advances in the field of biomedical text summarization. Different types of challenges are introduced, and methods are discussed concerning…
Small-world networks for summarization of biomedical articles
Milad Moradi
In recent years, many methods have been developed to identify important portions of text documents. Summarization tools can utilize these methods to extract summaries from large vo…