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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...
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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...
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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...
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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...
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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...
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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 ...
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08/27/2021
Deep learning models are not robust against noise in clinical text
Artificial Intelligence (AI) systems are attracting increasing interest ...
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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...
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08/16/2021
Hybrid deep learning methods for phenotype prediction from clinical notes
Identifying patient cohorts from clinical notes in secondary electronic ...
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12/20/2020
Explaining Black-box Models for Biomedical Text Classification
In this paper, we propose a novel method named Biomedical Confident Item...
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10/21/2020
Explaining black-box text classifiers for disease-treatment information extraction
Deep neural networks and other intricate Artificial Intelligence (AI) mo...
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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...
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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...
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08/06/2019
Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts
In recent years, summarizers that incorporate domain knowledge into the ...
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08/06/2019
Text Summarization in the Biomedical Domain
This chapter gives an overview of recent advances in the field of biomed...
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03/07/2019
Small-world networks for summarization of biomedical articles
In recent years, many methods have been developed to identify important ...
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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 ...
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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...
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05/10/2016
