Text data is indispensable for modern machine learning and natural language processing but often contains sensitive information that must be protected before sharing or release. Differential privacy (DP) provides rigorous guarantees for privacy prese...
Background: The recent rise of large language models has triggered renewed interest in medical free text data, which holds critical information about patients and diseases. However, medical free text is also highly sensitive. Therefore, de-identifica...
Medical data is an important part of modern medicine. However, with the rapid increase in the amount of data, it has become hard to use this data effectively. The development of machine learning, such as feature engineering, enables researchers to ca...
A major hurdle in the development of natural language processing (NLP) methods for Electronic Health Records (EHRs) is the lack of large, annotated datasets. Privacy concerns prevent the distribution of EHRs, and the annotation of data is known to be...
Large language models (LLMs) have transformed Natural Language Processing (NLP) by enabling robust text generation and understanding. However, their deployment in sensitive domains like healthcare, finance, and legal services raises critical concerns...
The internet’s evolution as a global communication nexus has enabled unprecedented connectivity, allowing users to share information, media, and personal updates across social platforms. However, these platforms also amplify risks such as cyber...
Machine reading comprehension (MRC) of text data is a challenging task in Natural Language Processing (NLP), with a lot of ongoing research fueled by the release of the Stanford Question Answering Dataset (SQuAD) and Conversational Question Answering...
Social networks generate vast amounts of data that can reveal patterns of human behaviour, social attachment, and mental states. This paper explores advanced machine learning techniques to detect and model such patterns, focusing on community structu...
Artificial Intelligence (AI) methodologies have profoundly influenced healthcare research, particularly in chronic disease management and public health. This paper provides a comprehensive state-of-the-art review of AI’s applications across dia...
Stance detection for low-resource languages, such as the Kuwaiti dialect, poses a significant challenge in natural language processing (NLP) due to the scarcity of annotated datasets and specialized tools. This study addresses these limitations by ev...
Encrypted traffic classification is a crucial part of privacy-preserving research. With the great success of artificial intelligence technology in fields such as image recognition and natural language processing, how to classify encrypted traffic bas...
This paper tackles the critical issue of privacy in Natural Language Processing (NLP) systems that process sensitive data by introducing a novel framework combining differential privacy and adversarial training. The proposed solution ensures formal p...
Email is an excellent technique for connecting users at low cost. Spam emails pose the risk of collecting a user’s personal information by fooling them into clicking on a link or engaging in other fraudulent activities. Furthermore, when a spam...
Pursuing “intelligent justice” necessitates an impartial, productive, and technologically driven methodology for judicial determinations. This scholarly composition proposes a framework that harnesses Artificial Intelligence (AI) innovati...
Data security is a critical concern for Internet users, primarily as more people rely on social networks and online tools daily. Despite the convenience, many users are unaware of the risks posed to their sensitive and personal data. This study addre...
Dataset distillation has become an important technique for enhancing the efficiency of data when training machine learning models. It finds extensive applications across various fields, including computer vision (CV) and natural language processing (...
14 May 2025
Artificial intelligence (AI) and assistive robotics can transform older-person care by offering new, personalised solutions for an ageing population. This paper outlines recent advances in AI-driven applications and robotic assistance in silver care,...