To identify and synthesise research on applications of natural language processing (NLP) for information extraction and retrieval from clinical notes in dentistry....
A predefined search strategy was applied in EMBASE, CINAHL and Medline. Studies eligible for inclusion were those that that described, evaluated, or applied NLP to clinical notes containing either hum...
Of the 17 included studies, 10 developed and evaluated NLP methods and 7 described applications of NLP-based information retrieval methods in dental records. Studies were published between 2015 and 20...
Study design heterogeneity and incomplete reporting of studies currently limits our ability to synthesise NLP applications in dental records. Standardisation of reporting and improved connections betw...
PROSPERO CRD42021227823....
There has been a growing emphasis on data across various health-related fields, not just in nursing research, due to the increasing volume of unstructured data in electronic health records (EHRs). Nat...
The integration of natural language processing (NLP) tools into neurology workflows has the potential to significantly enhance clinical care. However, it is important to address the limitations and ri...
To create a decision support tool based on machine learning algorithms and natural language processing (NLP) technology, to augment clinicians' ability to predict cases of suspected adnexal torsion....
Retrospective cohort study SETTING: Gynecology department, university-affiliated teaching medical center, 2014-2022....
This study assessed risk-factors for adnexal torsion among women managed surgically for suspected adnexal torsion based on clinical and sonographic data....
None....
The dataset included demographic, clinical, sonographic, and surgical information obtained from electronic medical records. NLP was used to extract insights from unstructured free text and unlock them...
Using machine learning algorithms and NLP technology as a decision-support tool for the diagnosis of adnexal torsion is feasible. It improved true prediction of adnexal torsion to 84% and decreased ca...
Revealing the function of uncharacterized genes is a fundamental challenge in an era of ever-increasing volumes of sequencing data. Here, we present a concept for tackling this challenge using deep le...
Natural language processing (NLP) is a wide range of techniques that allows computers to interact with human text. Applications of NLP in everyday life include language translation aids, chat bots, an...
The meaningful use of electronic health records (EHR) continues to progress in the digital era with clinical decision support systems augmented by artificial intelligence. A priority in improving prov...
With advances in deep learning and natural language processing (NLP), the analysis of medical texts is becoming increasingly important. Nonetheless, despite the importance of processing medical texts,...
A well-documented consequence of global warming is increased psychological distress and climate anxiety, but data gaps limit action. While climate anxiety garners attention, its expression in therapy ...
This study aims to use a novel technology based on natural language processing (NLP) to extract clinical information from electronic health records (EHRs) to characterise the clinical profile of patie...
An observational, retrospective analysis was conducted on EHR data from all patients with SpA (including psoriatic arthritis (PsA)) at Hospital Universitario La Paz, between 2020 and 2022. Data were c...
From a hospital population of 639 474 patients, 4337 (0.7%) patients had a diagnosis of SpA or their subtypes in their EHR. The population predominantly comprised men (55.3%) with a mean age of 50.9 y...
The application of NLP technology facilitated the characterisation of the SpA patient profile, including demographics, clinical features, comorbidities and treatments. This study supports the utility ...
