AIMC Topic: Natural Language Processing
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Clinical Prompt Learning With Frozen Language Models.
IEEE transactions on neural networks and learning systems
Oct 29, 2024
When the first transformer-based language models were published in the late 2010s, pretraining with general text and then fine-tuning the model on a task-specific dataset often achieved the state-of-the-art performance. However, more recent work sugg...
Biologically Plausible Sparse Temporal Word Representations.
IEEE transactions on neural networks and learning systems
Oct 29, 2024
Word representations, usually derived from a large corpus and endowed with rich semantic information, have been widely applied to natural language tasks. Traditional deep language models, on the basis of dense word representations, requires large mem...
Automated Extraction of Stroke Severity From Unstructured Electronic Health Records Using Natural Language Processing.
Journal of the American Heart Association
Oct 25, 2024
BACKGROUND: Multicenter electronic health records can support quality improvement and comparative effectiveness research in stroke. However, limitations of electronic health record-based research include challenges in abstracting key clinical variabl...
Demonstration-based learning for few-shot biomedical named entity recognition under machine reading comprehension.
Journal of biomedical informatics
Oct 25, 2024
OBJECTIVE: Although deep learning techniques have shown significant achievements, they frequently depend on extensive amounts of hand-labeled data and tend to perform inadequately in few-shot scenarios. The objective of this study is to devise a stra...
Use of Deep Learning to Identify Peripheral Arterial Disease Cases From Narrative Clinical Notes.
The Journal of surgical research
Oct 24, 2024
INTRODUCTION: Peripheral arterial disease (PAD) is the leading cause of amputation in the United States. Despite affecting 8.5 million Americans and more than 200 million people globally, there are significant gaps in awareness by both patients and p...
Harnessing explainable artificial intelligence for patient-to-clinical-trial matching: A proof-of-concept pilot study using phase I oncology trials.
PloS one
Oct 24, 2024
This study aims to develop explainable AI methods for matching patients with phase 1 oncology clinical trials using Natural Language Processing (NLP) techniques to address challenges in patient recruitment for improved efficiency in drug development....
Automated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing.
JACC. Heart failure
Oct 23, 2024
BACKGROUND: The lack of automated tools for measuring care quality limits the implementation of a national program to assess guideline-directed care in heart failure with reduced ejection fraction (HFrEF).
Accuracy of natural language processors for patients seeking inguinal hernia information.
Surgical endoscopy
Oct 23, 2024
BACKGROUND: NLPs such as ChatGPT are novel sources of online healthcare information that are readily accessible and integrated into internet search tools. The accuracy of NLP-generated responses to health information questions is unknown.
From pre-training to fine-tuning: An in-depth analysis of Large Language Models in the biomedical domain.
Artificial intelligence in medicine
Oct 23, 2024
In this study, we delve into the adaptation and effectiveness of Transformer-based, pre-trained Large Language Models (LLMs) within the biomedical domain, a field that poses unique challenges due to its complexity and the specialized nature of its da...
Enhancing Arabidopsis thaliana ubiquitination site prediction through knowledge distillation and natural language processing.
Methods (San Diego, Calif.)
Oct 22, 2024
Protein ubiquitination is a critical post-translational modification (PTM) involved in diverse biological processes and plays a pivotal role in regulating physiological mechanisms and disease states. Despite various efforts to develop ubiquitination ...
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