AIMC Topic: Natural Language Processing
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Leveraging Natural Language Processing to Improve Electronic Health Record Suicide Risk Prediction for Veterans Health Administration Users.
The Journal of clinical psychiatry
Jun 19, 2023
Suicide risk prediction models frequently rely on structured electronic health record (EHR) data, including patient demographics and health care usage variables. Unstructured EHR data, such as clinical notes, may improve predictive accuracy by allow...
ChatGPT and Other Natural Language Processing Artificial Intelligence Models in Adult Reconstruction.
The Journal of arthroplasty
Jun 17, 2023
Automatic Extraction of Comprehensive Drug Safety Information from Adverse Drug Event Narratives in the Korea Adverse Event Reporting System Using Natural Language Processing Techniques.
Drug safety
Jun 17, 2023
INTRODUCTION: Concerns have been raised over the quality of drug safety information, particularly data completeness, collected through spontaneous reporting systems (SRS), although regulatory agencies routinely use SRS data to guide their pharmacovig...
Let's be fair. What about an AI editor?
Accountability in research
Jun 15, 2023
Much of the current attention on artificial intelligence (AI)-based natural language processing (NLP) systems has focused on research ethics and integrity but neglects their roles in the editorial and peer-reviewing process. We argue that the academi...
Revolution of echocardiographic reporting: the new era of artificial intelligence and natural language processing.
Journal of echocardiography
Jun 13, 2023
Artificial intelligence (AI) has been making a significant impact on cardiovascular imaging, transforming everything from data capture to report generation. In the field of echocardiography, AI offers the potential to enhance accuracy, speed up repor...
Contextualized medication event extraction with striding NER and multi-turn QA.
Journal of biomedical informatics
Jun 13, 2023
This paper describes contextualized medication event extraction for automatically identifying medication change events with their contexts from clinical notes. The striding named entity recognition (NER) model extracts medication name spans from an i...
Integrating domain knowledge for biomedical text analysis into deep learning: A survey.
Journal of biomedical informatics
Jun 7, 2023
The past decade has witnessed an explosion of textual information in the biomedical field. Biomedical texts provide a basis for healthcare delivery, knowledge discovery, and decision-making. Over the same period, deep learning has achieved remarkable...
Health system-scale language models are all-purpose prediction engines.
Nature
Jun 7, 2023
Physicians make critical time-constrained decisions every day. Clinical predictive models can help physicians and administrators make decisions by forecasting clinical and operational events. Existing structured data-based clinical predictive models ...
Generalizability and portability of natural language processing system to extract individual social risk factors.
International journal of medical informatics
Jun 5, 2023
OBJECTIVE: The objective of this study is to validate and report on portability and generalizability of a Natural Language Processing (NLP) method to extract individual social factors from clinical notes, which was originally developed at a different...
Clinical named entity recognition and relation extraction using natural language processing of medical free text: A systematic review.
International journal of medical informatics
Jun 5, 2023
BACKGROUND: Natural Language Processing (NLP) applications have developed over the past years in various fields including its application to clinical free text for named entity recognition and relation extraction. However, there has been rapid develo...
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