Background and objectives Artificial intelligence (AI) has branched out to various
applications in healthcare, such as health services management, predictive medicine …

Much of the knowledge and information needed for enabling high-quality clinical research is
stored in free-text format. Natural language processing (NLP) has been used to extract …

Despite the myriad peer-reviewed papers demonstrating novel Artificial Intelligence (AI)-
based solutions to COVID-19 challenges during the pandemic, few have made a significant …

Clinical coding is the task of transforming medical information in a patient's health records
into structured codes so that they can be used for statistical analysis. This is a cognitive and …

Background Natural language processing (NLP) has a significant role in advancing
healthcare and has been found to be key in extracting structured information from radiology …

eXplainable AI (XAI) involves two intertwined but separate challenges: the development of
techniques to extract explanations from black-box AI models and the way such explanations …

Medical coding is the task of assigning medical codes to clinical free-text documentation.
Healthcare professionals manually assign such codes to track patient diagnoses and …

The recent literature in text classification is biased towards short text sequences (eg,
sentences or paragraphs). In real-world applications, multi-page multi-paragraph documents …

Automatic International Classification of Diseases (ICD) coding aims to assign multiple ICD
codes to a medical note with average length of 3,000+ tokens. This task is challenging due …

Unsupervised pretraining is an integral part of many natural language processing systems,
and transfer learning with language models has achieved remarkable results in downstream …