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Found 6 papers, 2 papers with code
Extracting Social Support and Social Isolation Information from Clinical Psychiatry Notes: Comparing a Rule-based NLP System and a Large Language Model
For extracting subcategories, the RBS also outperformed the LLM at both MSHS (0. 90 vs. 0. 62) and WCM (0. 82 vs. 0. 81).
Generative Large Language Models are autonomous practitioners of evidence-based medicine
Background: Evidence-based medicine (EBM) is fundamental to modern clinical practice, requiring clinicians to continually update their knowledge and apply the best clinical evidence in patient care.
Keyword-optimized Template Insertion for Clinical Information Extraction via Prompt-based Learning
This seems particularly important in the clinical setting, where task-relevant information is usually sparse in clinical notes.
reval: a Python package to determine best clustering solutions with stability-based relative clustering validation
Determining the best partition for a dataset can be a challenging task because of 1) the lack of a priori information within an unsupervised learning framework; and 2) the absence of a unique clustering validation approach to evaluate clustering solutions.
Deep Representation Learning of Electronic Health Records to Unlock Patient Stratification at Scale
With these results, we demonstrate that ConvAE can generate patient representations that lead to clinically meaningful insights.
Convolutional neural networks for structured omics: OmicsCNN and the OmicsConv layer
Convolutional Neural Networks (CNNs) are a popular deep learning architecture widely applied in different domains, in particular in classifying over images, for which the concept of convolution with a filter comes naturally.
