AI Medical Compendium Topic:
Area Under Curve

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Constructing synthetic datasets with generative artificial intelligence to train large language models to classify acute renal failure from clinical notes.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To compare performances of a classifier that leverages language models when trained on synthetic versus authentic clinical notes.

An interpretable predictive deep learning platform for pediatric metabolic diseases.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Metabolic disease in children is increasing worldwide and predisposes a wide array of chronic comorbid conditions with severe impacts on quality of life. Tools for early detection are needed to promptly intervene to prevent or slow the de...

What predicts citation counts and translational impact in headache research? A machine learning analysis.

Cephalalgia : an international journal of headache
BACKGROUND: We aimed to develop the first machine learning models to predict citation counts and the translational impact, defined as inclusion in guidelines or policy documents, of headache research, and assess which factors are most predictive.

HRGCNLDA: Forecasting of lncRNA-disease association based on hierarchical refinement graph convolutional neural network.

Mathematical biosciences and engineering : MBE
Long non-coding RNA (lncRNA) is considered to be a crucial regulator involved in various human biological processes, including the regulation of tumor immune checkpoint proteins. It has great potential as both a cancer biomolecular biomarker and ther...

Artificial Intelligence Approach for Severe Dengue Early Warning System.

Studies in health technology and informatics
Dengue fever is a viral infectious disease transmitted through mosquito bites, and has symptoms ranging from mild flu-like symptoms to deadly complications. Dengue fever is one of the global burden diseases which annually have 50-100 million cases wi...

Deep Learning for Midfacial Fracture Detection in CT Images.

Studies in health technology and informatics
This study deploys the deep learning-based object detection algorithms to detect midfacial fractures in computed tomography (CT) images. The object detection models were created using faster R-CNN and RetinaNet from 2,000 CT images. The best detectio...

A Fully Automated Deep-Learning Model for Predicting the Molecular Subtypes of Posterior Fossa Ependymomas Using T2-Weighted Images.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: We aimed to develop and validate a deep learning (DL) model to automatically segment posterior fossa ependymoma (PF-EPN) and predict its molecular subtypes [Group A (PFA) and Group B (PFB)] from preoperative MR images.

Prediction of Vancomycin-Associated Nephrotoxicity Based on the Area under the Concentration-Time Curve of Vancomycin: A Machine Learning Analysis.

Biological & pharmaceutical bulletin
Several machine learning models have been proposed to predict vancomycin (VCM)-associated nephrotoxicity; however, they have notable limitations. Specifically, they do not use the area under the concentration-time curve (AUC) as recommended in the la...

Diagnostic performance of machine-learning algorithms for sepsis prediction: An updated meta-analysis.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Early identification of sepsis has been shown to significantly improve patient prognosis.