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Natural Language Processing

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Compliance Evaluation with ChatGPT for Diagnosis and Treatment in Patients Brought to the ED with a Preliminary Diagnosis of Stroke.

Prehospital emergency care
OBJECTIVES: Chat Generative Pre-trained Transformer (ChatGPT) is a natural language processing product developed by OpenAI. Recently, the use of ChatGPT has gained attention in the field of health care, particularly for its potential applications in ...

Application of the LDA model to identify topics in telemedicine conversations on the X social network.

BMC health services research
The evolution experienced by global society, in the post-COVID 19 era, is marked by the quite obligatory use of digital media in many sectors, as is the case for the health sector. Quite frequently, both patients and health professionals use social m...

Assessing Total Hip Arthroplasty Outcomes and Generating an Orthopedic Research Outcome Database via a Natural Language Processing Pipeline: Development and Validation Study.

JMIR medical informatics
BACKGROUND: Processing data from electronic health records (EHRs) to build research-grade databases is a lengthy and expensive process. Modern arthroplasty practice commonly uses multiple sites of care, including clinics and ambulatory care centers. ...

Comparing neural language models for medical concept representation and patient trajectory prediction.

Artificial intelligence in medicine
Effective representation of medical concepts is crucial for secondary analyses of electronic health records. Neural language models have shown promise in automatically deriving medical concept representations from clinical data. However, the comparat...

[Technical foundations of large language models].

Radiologie (Heidelberg, Germany)
BACKGROUND: Large language models (LLMs) such as ChatGPT have rapidly revolutionized the way computers can analyze human language and the way we can interact with computers.

Leveraging large language models for knowledge-free weak supervision in clinical natural language processing.

Scientific reports
The performance of deep learning-based natural language processing systems is based on large amounts of labeled training data which, in the clinical domain, are not easily available or affordable. Weak supervision and in-context learning offer partia...

Position-context additive transformer-based model for classifying text data on social media.

Scientific reports
In recent years, the continuous increase in the growth of text data on social media has been a major reason to rely on the pre-training method to develop new text classification models specially transformer-based models that have proven worthwhile in...

Integration of large-scale community-developed causal loop diagrams: a Natural Language Processing approach to merging factors based on semantic similarity.

BMC public health
BACKGROUND: Complex public health problems have been addressed in communities through systems thinking and participatory methods like Group Model Building (GMB) and Causal Loop Diagrams (CLDs) albeit with some challenges. This study aimed to explore ...

NLP modeling recommendations for restricted data availability in clinical settings.

BMC medical informatics and decision making
BACKGROUND: Clinical decision-making in healthcare often relies on unstructured text data, which can be challenging to analyze using traditional methods. Natural Language Processing (NLP) has emerged as a promising solution, but its application in cl...