AI Medical Compendium Topic

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Immunophenotyping

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Measurement and immunophenotyping of pleural fluid EpCAM-positive cells and clusters for the management of non-small cell lung cancer patients.

Lung cancer (Amsterdam, Netherlands)
OBJECTIVES: A malignant pleural effusion (MPE) is a common complication in non-small cell lung cancer (NSCLC) with important staging and prognostic information. Patients with MPEs are often candidates for advanced therapies, however, the current gold...

flowCL: ontology-based cell population labelling in flow cytometry.

Bioinformatics (Oxford, England)
MOTIVATION: Finding one or more cell populations of interest, such as those correlating to a specific disease, is critical when analysing flow cytometry data. However, labelling of cell populations is not well defined, making it difficult to integrat...

Precision immunoprofiling by image analysis and artificial intelligence.

Virchows Archiv : an international journal of pathology
Clinical success of immunotherapy is driving the need for new prognostic and predictive assays to inform patient selection and stratification. This requirement can be met by a combination of computational pathology and artificial intelligence. Here, ...

Machine learning identifies an immunological pattern associated with multiple juvenile idiopathic arthritis subtypes.

Annals of the rheumatic diseases
OBJECTIVES: Juvenile idiopathic arthritis (JIA) is the most common class of childhood rheumatic diseases, with distinct disease subsets that may have diverging pathophysiological origins. Both adaptive and innate immune processes have been proposed a...

An ontology for representing hematologic malignancies: the cancer cell ontology.

BMC bioinformatics
BACKGROUND: Within the cancer domain, ontologies play an important role in the integration and annotation of data in order to support numerous biomedical tools and applications. This work seeks to leverage existing standards in immunophenotyping cell...

Automated Flow Cytometric MRD Assessment in Childhood Acute B- Lymphoblastic Leukemia Using Supervised Machine Learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Minimal residual disease (MRD) as measured by multiparameter flow cytometry (FCM) is an independent and strong prognostic factor in B-cell acute lymphoblastic leukemia (B-ALL). However, reliable flow cytometric detection of MRD strongly depends on op...