Abstract The AI-NLP models developed under the Text2RWD initiative are not only enhancing the development and anonymization of a particular medical dataset, but also have the potential to be shared and utilized in other medical fields. These models are being customized for tasks involving the analysis of unstructured text data found in oncological electronic health records within Galén, a system for... The AI-NLP models developed under the Text2RWD initiative are not only enhancing the development and anonymization of a particular medical dataset, but also have the potential to be shared and utilized in other medical fields. These models are being customized for tasks involving the analysis of unstructured text data found in oncological electronic health records within Galén, a system for managing healthcare information. They will be evaluated and confirmed by being applied to various clinically relevant tasks using real-world data from oncology departments. The AI-NLP models are also projected to be shared and utilized in analysing text databases from other medical fields or healthcare environments to validate their effectiveness in extracting information and predicting outcomes in these specific domains. Read More Read Less

Abstract As the primary method for sharing information, Natural Language Processing (NLP) stands as a crucial technology in today’s digital revolution. Over the past few years, the field of NLP has played a significant role in developing advanced deep-learning methods and tools that transform how we tackle tasks related to Language Technology (LT). NLP has evolved from a traditional approach that... As the primary method for sharing information, Natural Language Processing (NLP) stands as a crucial technology in today’s digital revolution. Over the past few years, the field of NLP has played a significant role in developing advanced deep-learning methods and tools that transform how we tackle tasks related to Language Technology (LT). NLP has evolved from a traditional approach that relied on a series of interconnected modules for solutions to a more sophisticated model based on intricate neural networks, all trained on extensive text data. These recent developments have led to a significant shift in the approach to creating and utilizing large, pre-trained transformer-based language models. The outcomes have been so remarkable that systems are now achieving human-level performance in certain challenging language comprehension tasks. However, these large language models present significant challenges. There is a lack of understanding regarding their inner workings, failure points, and how to enhance their capabilities further. It’s crucial to recognise the constraints of these large language models. DeepKnowledge aims to explore the pre-training of large language models for the official languages of Spain, employing innovative methods to extract more detailed and applicable knowledge. Read More Read Less

Abstract This article aims to build a web-based college English reading self-learning platform based on the campus network in order to improve students’ English reading and self-learning abilities. This platform provides students with an autonomous learning environment that integrates various functions such as online learning, testing, and communication. This article first introduces the background and significance of the platform’s construction and... This article aims to build a web-based college English reading self-learning platform based on the campus network in order to improve students’ English reading and self-learning abilities. This platform provides students with an autonomous learning environment that integrates various functions such as online learning, testing, and communication. This article first introduces the background and significance of the platform’s construction and then elaborates on the platform’s architecture design, functional implementation, and technical characteristics in detail. Finally, the effectiveness and superiority of the platform were verified through experiments, and the results showed that the platform can significantly improve students’ English reading ability and autonomous learning ability. Read More Read Less