Development and Validation of a Model to Identify Critical Brain Injuries Using Natural Language Processing of Text Computed Tomography Reports.

Importance: Clinical text reports from head computed tomography (CT) represent rich, incompletely utilized information regarding acute brain injuries and neurologic outcomes. CT reports are unstructured; thus, extracting information at scale requires automated natural language processing (NLP). However, designing new NLP algorithms for each individual injury category is an unwieldy proposition.

[Expression of p29, estrogen receptor related protein in primary breast carcinoma. Methodological, anatomoclinical, and DNA content analysis].

The aim of this work was to assess the immunohistochemical detection of a estrogen receptor related protein (p29) in 48 histological samples of primary mammary carcinoma and its relationship to clinical, morphological and ADN content parameters. p29 protein was positive in 62.5% of samples.

[Breast cancer and flow cytometry: comparative study of DNA ploidy pattern with clinicopathological parameters].

There is evidence that DNA quantization and histopathological classification of breast cancer may be useful for its therapeutic management. DNA flow cytometry, clinical and anatomopathological features of 60 paraffin embedded primary breast cancer tissue samples were studied. The aneuploidy percentage was 67%.