Natural language processing with machine learning methods to analyze unstructured patient-reported outcomes derived from electronic health records: A systematic …
Objective Natural language processing (NLP) combined with machine learning (ML)
techniques are increasingly used to process unstructured/free-text patient-reported outcome …
techniques are increasingly used to process unstructured/free-text patient-reported outcome …
[HTML][HTML] Clinical named entity recognition and relation extraction using natural language processing of medical free text: A systematic review
Abstract Background Natural Language Processing (NLP) applications have developed
over the past years in various fields including its application to clinical free text for named …
over the past years in various fields including its application to clinical free text for named …
Towards a universal privacy model for electronic health record systems: an ontology and machine learning approach
This paper proposed a novel privacy model for Electronic Health Records (EHR) systems
utilizing a conceptual privacy ontology and Machine Learning (ML) methodologies. It …
utilizing a conceptual privacy ontology and Machine Learning (ML) methodologies. It …
A building regulation question answering system: A deep learning methodology
Regulations play an important role in assuring the quality of a building's construction and
minimizing its adverse environmental impacts. Engineers and the like need to retrieve …
minimizing its adverse environmental impacts. Engineers and the like need to retrieve …
Semantic web-based diagnosis and treatment of vector-borne diseases using SWRL rules
Vector-borne diseases (VBDs) are a kind of infection caused through the transmission of
vectors generated by the bites of infected parasites, bacteria, and viruses, such as ticks …
vectors generated by the bites of infected parasites, bacteria, and viruses, such as ticks …
Systematic literature review of information extraction from textual data: recent methods, applications, trends, and challenges
Information extraction (IE) is a challenging task, particularly when dealing with highly
heterogeneous data. State-of-the-art data mining technologies struggle to process …
heterogeneous data. State-of-the-art data mining technologies struggle to process …
[HTML][HTML] AI in dermatology: a comprehensive review into skin cancer detection
Background Artificial Intelligence (AI) is significantly transforming dermatology, particularly in
early skin cancer detection and diagnosis. This technological advancement addresses a …
early skin cancer detection and diagnosis. This technological advancement addresses a …
Measurement extraction with natural language processing: a review
Quantitative data is important in many domains. Information extraction methods draw
structured data from documents. However, the extraction of quantities and their contexts has …
structured data from documents. However, the extraction of quantities and their contexts has …
Model validation using invariant signatures and logic-based inference for automated building code compliance checking
Fully automated building code compliance checking (ACC) requires accurate information
extraction from both building information models (BIMs) and building code chapters, and …
extraction from both building information models (BIMs) and building code chapters, and …
Automated detection of causal relationships among diseases and imaging findings in textual radiology reports
RA Sebro, CE Kahn Jr - Journal of the American Medical …, 2023 - academic.oup.com
Objective Textual radiology reports contain a wealth of information that may help understand
associations among diseases and imaging observations. This study evaluated the ability to …
associations among diseases and imaging observations. This study evaluated the ability to …