The implementation of Data Analytics has achieved a significant momentum across a very
wide range of domains. Part of that progress is directly linked to the implementation of Text …

Objective: The aim of this study was to systematically assess the application and potential
benefits of natural language processing (NLP) in surgical outcomes research. Summary …

Problem: Clinical practice requires the production of a time-and resource-consuming great
amount of notes. They contain relevant information, but their secondary use is almost …

Natural language processing (NLP), a domain of artificial intelligence (AI) that models
human language, has been used in medicine to automate diagnostics, detect adverse …

Background The systematic collection of valid data related to hospital-acquired infections
(HAIs) is considered effective for nosocomial infection prevention and control programs …

Infections encompass a set of medical conditions of very diverse kinds that can pose a
significant risk to health, and even death. As with many other diseases, early diagnosis can …

Background In patients who underwent colorectal surgery, an existing semi-automated
surveillance algorithm based on structured data achieves high sensitivity in detecting deep …

This paper proposes an artificial intelligence model to manage risks in healthcare
institutions. This model uses a trendy data source, social media, and employs users' …

Named entity recognition (NER) is key for biomedical applications as it allows knowledge
discovery in free text data. As entities are semantic phrases, their meaning is conditioned to …

Natural Language Processing (NLP) is the computerized approach to analyzing text using
both structured and unstructured data. NLP is a simple, empirically powerful, and reliable …