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Natural Language Processing

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Image captioning in Bengali language using visual attention.

PloS one
Automatically generating image captions poses one of the most challenging applications within artificial intelligence due to its integration of computer vision and natural language processing algorithms. This task becomes notably more formidable when...

Empowering large language models for automated clinical assessment with generation-augmented retrieval and hierarchical chain-of-thought.

Artificial intelligence in medicine
BACKGROUND: Understanding and extracting valuable information from electronic health records (EHRs) is important for improving healthcare delivery and health outcomes. Large language models (LLMs) have demonstrated significant proficiency in natural ...

Neuradicon: Operational representation learning of neuroimaging reports.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Radiological reports typically summarize the content and interpretation of imaging studies in unstructured form that precludes quantitative analysis. This limits the monitoring of radiological services to throughput undiffer...

Natural language processing techniques applied to the electronic health record in clinical research and practice - an introduction to methodologies.

Computers in biology and medicine
Natural Language Processing (NLP) has the potential to revolutionise clinical research utilising Electronic Health Records (EHR) through the automated analysis of unstructured free text. Despite this potential, relatively few applications have entere...

Using Natural Language Processing Methods to Predict Topics Included in 2019 Ohio Syphilis Disease Intervention Specialist Records.

Sexually transmitted diseases
BACKGROUND: Free-text notes in disease intervention specialist (DIS) records may contain relevant information for sexual transmitted infection control. In their current form, the notes are not analyzable without manual reading, which is labor-intensi...

[Transformation of free-text radiology reports into structured data].

Radiologie (Heidelberg, Germany)
BACKGROUND: The rapid development of large language models (LLMs) opens up new possibilities for the automated processing of medical texts. Transforming unstructured radiology reports into structured data is crucial for efficient use in clinical deci...

Cost-Efficient Domain-Adaptive Pretraining of Language Models for Optoelectronics Applications.

Journal of chemical information and modeling
Pretrained language models have demonstrated strong capability and versatility in natural language processing (NLP) tasks, and they have important applications in optoelectronics research, such as data mining and topic modeling. Many language models ...

Developing an ICD-10 Coding Assistant: Pilot Study Using RoBERTa and GPT-4 for Term Extraction and Description-Based Code Selection.

JMIR formative research
BACKGROUND: The International Classification of Diseases (ICD), developed by the World Health Organization, standardizes health condition coding to support health care policy, research, and billing, but artificial intelligence automation, while promi...

RespBERT: A Multi-Site Validation of a Natural Language Processing Algorithm, of Radiology Notes to Identify Acute Respiratory Distress Syndrome (ARDS).

IEEE journal of biomedical and health informatics
Acute respiratory distress syndrome (ARDS) is a severe organ dysfunction associated with significant mortality and morbidity among critically ill patients admitted to the Intensive Care Unit (ICU). The etiology related to ARDS can be highly heterogen...

Partial Annotation Learning for Biomedical Entity Recognition.

IEEE journal of biomedical and health informatics
Named Entity Recognition (NER) is a key task to support biomedical research. In Biomedical Named Entity Recognition (BioNER), obtaining high-quality expert annotated data is laborious and expensive, leading to the development of automatic approaches ...