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M. Moradi

22 papers hereh-index 221.7k citations98 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author2
  • first author13
  • middle author4
  • last author3

Across the 22 of 22 papers where every author was matched, so the position is known.

fields
  • cs.CL11
  • cs.AI6
  • cs.IR2
  • cs.CV1
  • cs.DC1
  • cs.SE1
same name
  • M. Moradi — 7 papers, h 6
  • M. Moradi — 4 papers, h 24
  • M. Moradi — 4 papers, h 2
  • M. Moradi — 3 papers, h 10
  • M. Moradi — 3 papers, h 5
  • M. Moradi — 2 papers, h 24

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162024
most citedPost-hoc explanation of black-box classifiers using confident itemsets

122 citations · 259 across the 14 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.AI2020★ 27 cited

Explaining Black-box Models for Biomedical Text Classification

Milad Moradi, Matthias Samwald

In this paper, we propose a novel method named Biomedical Confident Itemsets Explanation (BioCIE), aiming at post-hoc explanation of black-box machine learning models for biomedica…

cs.AI2020

Explaining black-box text classifiers for disease-treatment information extraction

Milad Moradi, Matthias Samwald

Deep neural networks and other intricate Artificial Intelligence (AI) models have reached high levels of accuracy on many biomedical natural language processing tasks. However, the…

cs.AI2020

A critical analysis of metrics used for measuring progress in artificial intelligence

Kathrin Blagec, Georg Dorffner, Milad Moradi +1

Comparing model performances on benchmark datasets is an integral part of measuring and driving progress in artificial intelligence. A model's performance on a benchmark dataset is…

cs.AI2020★ 122 cited

Post-hoc explanation of black-box classifiers using confident itemsets

Milad Moradi, Matthias Samwald

Black-box Artificial Intelligence (AI) methods, e.g. deep neural networks, have been widely utilized to build predictive models that can extract complex relationships in a dataset…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.