AIMC Topic: National Cancer Institute (U.S.)

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Relating Complexity and Error Rates of Ontology Concepts. More Complex NCIt Concepts Have More Errors.

Methods of information in medicine Feb 28, 2017
OBJECTIVES: Ontologies are knowledge structures that lend support to many health-information systems. A study is carried out to assess the quality of ontological concepts based on a measure of their complexity. The results show a relation between com...
Humans Computer Simulation Neoplasms United States Models, Statistical Natural Language Processing Quality Assurance, Health Care Biological Ontologies Comprehension Vocabulary, Controlled Meaningful Use National Cancer Institute (U.S.)
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Machine learning and deep learning tools for the automated capture of cancer surveillance data.

Journal of the National Cancer Institute. Monographs Aug 1, 2024
The National Cancer Institute and the Department of Energy strategic partnership applies advanced computing and predictive machine learning and deep learning models to automate the capture of information from unstructured clinical text for inclusion ...
Humans Machine Learning Neoplasms Deep Learning United States Registries National Cancer Institute (U.S.)
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National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence.

Radiographics : a review publication of the Radiological Society of North America, Inc Dec 1, 2023
The remarkable advances of artificial intelligence (AI) technology are revolutionizing established approaches to the acquisition, interpretation, and analysis of biomedical imaging data. Development, validation, and continuous refinement of AI tools ...
Humans Artificial Intelligence Reproducibility of Results Neoplasms Multiomics United States Diagnostic Imaging National Cancer Institute (U.S.)
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Using ChatGPT to evaluate cancer myths and misconceptions: artificial intelligence and cancer information.

JNCI cancer spectrum Mar 1, 2023
Data about the quality of cancer information that chatbots and other artificial intelligence systems provide are limited. Here, we evaluate the accuracy of cancer information on ChatGPT compared with the National Cancer Institute's (NCI's) answers by...
Humans Artificial Intelligence Neoplasms United States National Cancer Institute (U.S.)
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Preliminary Analysis of Difficulty of Importing Pattern-Based Concepts into the National Cancer Institute Thesaurus.

Studies in health technology and informatics Jan 1, 2016
Maintenance of biomedical ontologies is difficult. We have developed a pattern-based method for dealing with the problem of identifying missing concepts in the National Cancer Institute thesaurus (NCIt). Specifically, we are mining patterns connectin...
Algorithms United States Biological Ontologies Vocabulary, Controlled National Cancer Institute (U.S.)
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