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Natural Language Processing

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Improving entity recognition using ensembles of deep learning and fine-tuned large language models: A case study on adverse event extraction from VAERS and social media.

Journal of biomedical informatics
OBJECTIVE: Adverse event (AE) extraction following COVID-19 vaccines from text data is crucial for monitoring and analyzing the safety profiles of immunizations, identifying potential risks and ensuring the safe use of these products. Traditional dee...

A foundation systematic review of natural language processing applied to gastroenterology & hepatology.

BMC gastroenterology
OBJECTIVE: This review assesses the progress of NLP in gastroenterology to date, grades the robustness of the methodology, exposes the field to a new generation of authors, and highlights opportunities for future research.

Larger models yield better results? Streamlined severity classification of ADHD-related concerns using BERT-based knowledge distillation.

PloS one
This work focuses on the efficiency of the knowledge distillation approach in generating a lightweight yet powerful BERT-based model for natural language processing (NLP) applications. After the model creation, we applied the resulting model, LastBER...

Evaluating the Efficacy of Perplexity Scores in Distinguishing AI-Generated and Human-Written Abstracts.

Academic radiology
RATIONALE AND OBJECTIVES: We aimed to evaluate the efficacy of perplexity scores in distinguishing between human-written and AI-generated radiology abstracts and to assess the relative performance of available AI detection tools in detecting AI-gener...

A Looking Glass into a Research Wonderland: Decades of Virtual Reality Scholarship Explicated Via Natural Language Processing.

Cyberpsychology, behavior and social networking
How has the field of virtual reality (VR) evolved and what type of research has made an impact? We used natural language processing techniques and generative artificial intelligence to develop the most complete review of experimental social science V...

HiRXN: Hierarchical Attention-Based Representation Learning for Chemical Reaction.

Journal of chemical information and modeling
In recent years, natural language processing (NLP) techniques, including large language modeling (LLM), have contributed significantly to advancements in organic chemistry research. Chemical reaction representations provide a link between NLP models ...

Information Extraction from Clinical Texts with Generative Pre-trained Transformer Models.

International journal of medical sciences
Processing and analyzing clinical texts are challenging due to its unstructured nature. This study compared the performance of GPT (Generative Pre-trained Transformer)-3.5 and GPT-4 for extracting information from clinical text. Three types of clin...

NLP for Analyzing Electronic Health Records and Clinical Notes in Cancer Research: A Review.

Journal of pain and symptom management
This review examines the application of natural language processing (NLP) techniques in cancer research using electronic health records (EHRs) and clinical notes. It addresses gaps in existing literature by providing a broader perspective than previo...

Using natural language processing to identify patterns associated with depression, anxiety, and stress symptoms during the COVID-19 pandemic.

Journal of affective disorders
BACKGROUND: Combining data-driven natural language processing techniques with traditional methods using predefined word lists may offer greater insights into the connections between language patterns and depression and anxiety symptoms, particularly ...

MechBERT: Language Models for Extracting Chemical and Property Relationships about Mechanical Stress and Strain.

Journal of chemical information and modeling
Language models are transforming materials-aware natural-language processing by enabling the extraction of dynamic, context-rich information from unstructured text, thus, moving beyond the limitations of traditional information-extraction methods. Mo...