Deep learning has become a leading subset of machine learning and has been successfully employed in diverse areas, ranging from natural language processing to medical image analysis. In medical imaging, researchers have progressively turned towards m...
IEEE journal of biomedical and health informatics
Oct 5, 2023
This study presents three deidentified large medical text datasets, named DISCHARGE, ECHO and RADIOLOGY, which contain 50 K, 16 K and 378 K pairs of report and summary that are derived from MIMIC-III, respectively. We implement convincing baselines o...
IEEE transactions on neural networks and learning systems
Oct 5, 2023
Artificial intelligence and machine learning techniques have progressed dramatically and become powerful tools required to solve complicated tasks, such as computer vision, speech recognition, and natural language processing. Since these techniques h...
Neural networks : the official journal of the International Neural Network Society
Sep 30, 2023
The prevalence of multivariate time series data across several disciplines fosters a demand and, subsequently, significant growth in the research and advancement of multivariate time series analysis. Drawing inspiration from a popular natural languag...
BACKGROUND: This study aimed to examine the accuracy with which multiple natural language processing artificial intelligence models could predict discharge and readmissions after general surgery.
Neural networks : the official journal of the International Neural Network Society
Sep 29, 2023
A significant amount of textual data has been produced in the biomedical area recently as a result of the advancement of biomedical technologies. Large-scale biomedical data can be automatically obtained with the help of distant supervision. However,...
A log-likelihood based co-occurrence analysis of ∼1.9 million de-identified ICD-10 codes and related short textual problem list entries generated possible term candidates at a significance level of p<0.01. These top 10 term candidates, consisting of ...
In recent years, pre-trained language models (PLMs) have dominated natural language processing (NLP) and achieved outstanding performance in various NLP tasks, including dense retrieval based on PLMs. However, in the biomedical domain, the effectiven...
OBJECTIVE: To develop and validate TraumaICDBERT, a natural language processing algorithm to predict injury International Classification of Diseases, 10th edition (ICD-10) diagnosis codes from trauma tertiary survey notes.
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