AIMC Topic: Natural Language Processing

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Sentiment analysis of the Hamas-Israel war on YouTube comments using deep learning.

Scientific reports
Sentiment analysis aims to classify text based on the opinion or mentality expressed in a situation, which can be positive, negative, or neutral. Therefore, in the world, a lot of opinions are available on various social media sites, which must be ga...

Text-to-video generative artificial intelligence: sora in neurosurgery.

Neurosurgical review
Artificial intelligence (AI) has increased in popularity in neurosurgery, with recent interest in generative AI algorithms such as the Large Language Model (LLM) ChatGPT. Sora, an innovation in generative AI, leverages natural language processing, de...

Exploring the Use of Natural Language Processing to Understand Emotions of Trainees and Faculty Regarding Entrustable Professional Activity Assessments.

Journal of graduate medical education
In medical education, artificial intelligence techniques such as natural language processing (NLP) are starting to be used to capture and analyze emotions through written text. To explore the application of NLP techniques to understand resident and...

HyGloadAttack: Hard-label black-box textual adversarial attacks via hybrid optimization.

Neural networks : the official journal of the International Neural Network Society
Hard-label black-box textual adversarial attacks present a highly challenging task due to the discrete and non-differentiable nature of text data and the lack of direct access to the model's predictions. Research in this issue is still in its early s...

A multimodal generative AI copilot for human pathology.

Nature
Computational pathology has witnessed considerable progress in the development of both task-specific predictive models and task-agnostic self-supervised vision encoders. However, despite the explosive growth of generative artificial intelligence (AI)...

Location-enhanced syntactic knowledge for biomedical relation extraction.

Journal of biomedical informatics
Biomedical relation extraction has long been considered a challenging task due to the specialization and complexity of biomedical texts. Syntactic knowledge has been widely employed in existing research to enhance relation extraction, providing guida...

End-to-end pseudonymization of fine-tuned clinical BERT models : Privacy preservation with maintained data utility.

BMC medical informatics and decision making
Many state-of-the-art results in natural language processing (NLP) rely on large pre-trained language models (PLMs). These models consist of large amounts of parameters that are tuned using vast amounts of training data. These factors cause the model...

Improving biomedical Named Entity Recognition with additional external contexts.

Journal of biomedical informatics
OBJECTIVE: Biomedical Named Entity Recognition (bio NER) is the task of recognizing named entities in biomedical texts. This paper introduces a new model that addresses bio NER by considering additional external contexts. Different from prior methods...

From Pixels to Principles: A Decade of Progress and Landscape in Trustworthy Computer Vision.

Science and engineering ethics
The rapid development of computer vision technologies and applications has brought forth a range of social and ethical challenges. Due to the unique characteristics of visual technology in terms of data modalities and application scenarios, computer ...