The project is in the incubation stage and still under development. ForteHealth is a flexible and powerful ML workflow builder for biomedical and clinical scenarios. This is part of the CASL project: http://casl-project.ai/
Apache License 2.0
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Create an example for medical text understanding #65
The idea is mainly for Abbreviation detection and Hyponym detection.
For example, the sample text is from wikipedia, Source:
Sample text:
Appropriately treating underlying illnesses (such as HIV/AIDS, diabetes mellitus, and malnutrition) (HYPONYM) can decrease the risk of pneumonia.[24][84][87] In children less than 6 months of age, exclusive breast feeding reduces both the risk and severity of disease.[24] In people with HIV/AIDS and a CD4 count of less than 200 cells/uL the antibiotic trimethoprim/sulfamethoxazole decreases the risk of Pneumocystis pneumonia[88] and is also useful for prevention in those that are immunocompromised but do not have HIV.[89]
Abbreviation includes HIV, AIDS, CD4, …
Possible included components:
Abbr detection
hyponym detection
Coreference resolution
(Other processors that can help text understanding can be added as well)
The idea is mainly for Abbreviation detection and Hyponym detection.
For example, the sample text is from wikipedia, Source:
Sample text: Appropriately treating
underlying illnesses (such as HIV/AIDS, diabetes mellitus, and malnutrition) (HYPONYM)can decrease the risk of pneumonia.[24][84][87] In children less than 6 months of age, exclusive breast feeding reduces both the risk and severity of disease.[24] In people with HIV/AIDS and a CD4 count of less than 200 cells/uL the antibiotic trimethoprim/sulfamethoxazole decreases the risk of Pneumocystis pneumonia[88] and is also useful for prevention in those that are immunocompromised but do not have HIV.[89]Abbreviation includes HIV, AIDS, CD4, …Possible included components:
(Other processors that can help text understanding can be added as well)