AIMC Topic: Natural Language Processing

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Assessing domain adaptation in adverse drug event extraction on real-world breast cancer records.

International journal of medical informatics
BACKGROUND: Adverse Drug Events (ADE) are key information present in unstructured portions of Electronic Health Records. These pose a significant challenge in healthcare, ranging from mild discomfort to severe complications, and can impact patient sa...

Mining core information by evaluating semantic importance for unpaired image captioning.

Neural networks : the official journal of the International Neural Network Society
Recently, exciting progress has been made in the research of supervised image captioning. However, manually annotated image-annotation pair data is difficult and expensive to obtain. Therefore, unpaired image captioning becomes an emerging challenge....

From vision to text: A comprehensive review of natural image captioning in medical diagnosis and radiology report generation.

Medical image analysis
Natural Image Captioning (NIC) is an interdisciplinary research area that lies within the intersection of Computer Vision (CV) and Natural Language Processing (NLP). Several works have been presented on the subject, ranging from the early template-ba...

Evolution of Drug Development and Regulatory Affairs: The Demonstrated Power of Artificial Intelligence.

Clinical therapeutics
PURPOSE: Artificial intelligence (AI) refers to technology capable of mimicking human cognitive functions and has important applications across all sectors and industries, including drug development. This has considerable implications for the regulat...

Prediction of intra-abdominal injury using natural language processing of electronic medical record data.

Surgery
BACKGROUND: This study aimed to use natural language processing to predict the presence of intra-abdominal injury using unstructured data from electronic medical records.

Clinical efficacy of pre-trained large language models through the lens of aphasia.

Scientific reports
The rapid development of large language models (LLMs) motivates us to explore how such state-of-the-art natural language processing systems can inform aphasia research. What kind of language indices can we derive from a pre-trained LLM? How do they d...

Neuroimaging and natural language processing-based classification of suicidal thoughts in major depressive disorder.

Translational psychiatry
Suicide is a growing public health problem around the world. The most important risk factor for suicide is underlying psychiatric illness, especially depression. Detailed classification of suicide in patients with depression can greatly enhance perso...

Risk factors for prediabetes in community-dwelling adults: A generalized estimating equation logistic regression approach with natural language processing insights.

Research in nursing & health
The global prevalence of prediabetes is expected to reach 8.3% (587 million people) by 2045, with 70% of people with prediabetes developing diabetes during their lifetimes. We aimed to classify community-dwelling adults with a high risk for prediabet...