Objective Our objective was to develop a machine learning-based system to determine the
severity of Positive Valance symptoms for a patient, based on information included in their …

Natural language processing is an exciting and emerging field in health care that can
transform the field of orthopaedics. It can aid in the process of automated clinical data …

To investigate consistency in summaries of product characteristics (Sm PC s) of generic
antimicrobials, we used natural language processing (NLP) to analyze and compare large …

Important information for public health is contained within Electronic Health Records (EHRs).
The vast majority of clinical data available in these records takes the form of narratives …

Identifying relevant studies and harmonizing datasets are major hurdles for data reuse.
Common Data Elements (CDEs) can help identify comparable study datasets and reduce …

Sample size calculation is an essential step in most data-based disciplines. Large enough
samples ensure representativeness of the population and determine the precision of …

The aim of this paper is to deeply analyze the unexpected side effects of people during the
Covid-19 pandemic using the RNN based NLP sentiment analysis model. The normalized …

The significance of integrating Natural Language Processing (NLP) approaches in
healthcare research has become more prominent in recent years, and it has had a …

This paper describes a theory derivation process used to develop a conceptual framework
for medication therapy management (MTM) research. The MTM service model and chronic …

Healthcare professionals are generating a substantial volume of clinical data in narrative
form. As healthcare providers are confronted with serious time constraints, they frequently …