Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039124
Multiple instance learning(MIL) has shown superior performance in the classification of whole-slide images(WSIs). The implementation of multiple instance learning for WSI classification typically involves two components, i.e., a feature extractor, wh...
Technology and health care : official journal of the European Society for Engineering and Medicine
40105161
BackgroundData discretization is an important preprocessing step in data mining for the transfer of continuous feature values to discrete ones, which allows some specific data mining algorithms to construct more effective models and facilitates the d...
Experimental biology and medicine (Maywood, N.J.)
40093658
Topic modeling is a crucial technique in natural language processing (NLP), enabling the extraction of latent themes from large text corpora. Traditional topic modeling, such as Latent Dirichlet Allocation (LDA), faces limitations in capturing the se...
This study aims to demonstrate that text phrase-mining and natural language processing (NLP) can annotate huge quantities of obstetrics textual data for the discovery and evaluation of maternal protein/gene (MPG)-disease interactions involved in the ...
BMC medical informatics and decision making
40098129
BACKGROUND: The HELLP syndrome represents three complications: hemolysis, elevated liver enzymes, and low platelet count. Since the causes and pathogenesis of HELLP syndrome are not yet fully known and well understood, distinguishing it from other pr...
SUMMARY: The lit-OTAR framework, developed through a collaboration between Europe PMC and Open Targets, leverages deep learning to revolutionize drug discovery by extracting evidence from scientific literature for drug target identification and valid...
Manually converting unstructured text pathology reports into structured pathology reports is very time-consuming and prone to errors. This study demonstrates the transformative potential of generative AI in automating the analysis of free-text pathol...
BMC medical informatics and decision making
40055729
BACKGROUND: Retinal vein occlusion (RVO) is a leading cause of vision loss globally. Routine health check-up data-including demographic information, medical history, and laboratory test results-are commonly utilized in clinical settings for disease r...
BACKGROUND: Patients' oral expressions serve as valuable sources of clinical information to improve pharmacotherapy. Natural language processing (NLP) is a useful approach for analyzing unstructured text data, such as patient narratives. However, few...
OBJECTIVE: As one of the most crucial upstream tasks in biomedical informatics, biomedical named entity normalization (BNEN) aims to map mentioned named entities to uniform standard identifiers or terms. Most existing methods only consider the simila...