Milad Moradi | DeepAI

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∙ 03/30/2023

Model-agnostic explainable artificial intelligence for object detection in image data

Object detection is a fundamental task in computer vision, which has bee...

0 Milad Moradi, et al. ∙

∙ 01/27/2023

ThoughtSource: A central hub for large language model reasoning data

Large language models (LLMs) such as GPT-3 and ChatGPT have recently dem...

0 Simon Ott, et al. ∙

∙ 04/25/2022

A global analysis of metrics used for measuring performance in natural language processing

Measuring the performance of natural language processing models is chall...

0 Kathrin Blagec, et al. ∙

∙ 02/25/2022

Deep Learning, Natural Language Processing, and Explainable Artificial Intelligence in the Biomedical Domain

In this article, we first give an introduction to artificial intelligenc...

0 Milad Moradi, et al. ∙

∙ 11/16/2021

Improving the robustness and accuracy of biomedical language models through adversarial training

Deep transformer neural network models have improved the predictive accu...

0 Milad Moradi, et al. ∙

∙ 09/06/2021

GPT-3 Models are Poor Few-Shot Learners in the Biomedical Domain

Deep neural language models have set new breakthroughs in many tasks of ...

0 Milad Moradi, et al. ∙

∙ 08/27/2021

Deep learning models are not robust against noise in clinical text

Artificial Intelligence (AI) systems are attracting increasing interest ...

0 Milad Moradi, et al. ∙

∙ 08/27/2021

Evaluating the Robustness of Neural Language Models to Input Perturbations

High-performance neural language models have obtained state-of-the-art r...

0 Milad Moradi, et al. ∙

∙ 08/16/2021

Hybrid deep learning methods for phenotype prediction from clinical notes

Identifying patient cohorts from clinical notes in secondary electronic ...

0 Sahar Khalafi, et al. ∙

∙ 12/20/2020

Explaining Black-box Models for Biomedical Text Classification

In this paper, we propose a novel method named Biomedical Confident Item...

0 Milad Moradi, et al. ∙

∙ 10/21/2020

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

Deep neural networks and other intricate Artificial Intelligence (AI) mo...

0 Milad Moradi, et al. ∙

∙ 08/06/2020

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

Comparing model performances on benchmark datasets is an integral part o...

36 Kathrin Blagec, et al. ∙

∙ 05/05/2020

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

It is difficult to trust decisions made by Black-box Artificial Intellig...

0 Milad Moradi, et al. ∙

∙ 08/06/2019

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts

In recent years, summarizers that incorporate domain knowledge into the ...

0 Milad Moradi, et al. ∙

∙ 08/06/2019

Text Summarization in the Biomedical Domain

This chapter gives an overview of recent advances in the field of biomed...

0 Milad Moradi, et al. ∙

∙ 03/07/2019

Small-world networks for summarization of biomedical articles

In recent years, many methods have been developed to identify important ...

0 Milad Moradi, et al. ∙

∙ 12/08/2017

A Method for Finding Similar Documents Relying on Adding Repetition of Symbols in Length Based Filtering

A basic topic in mining of massive dataset is finding similar items. As ...

0 Hossein Azgomi, et al. ∙

∙ 09/11/2016

A centralized reinforcement learning method for multi-agent job scheduling in Grid

One of the main challenges in Grid systems is designing an adaptive, sca...

0 Milad Moradi, et al. ∙

∙ 05/10/2016

Different approaches for identifying important concepts in probabilistic biomedical text summarization

Automatic text summarization tools help users in biomedical domain to ac...

0 Milad Moradi, et al. ∙

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