AIMC Topic: Immunophenotyping
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Machine learning-assisted immune profiling stratifies peri-implantitis patients with unique microbial colonization and clinical outcomes.
Theranostics
May 3, 2021
The endemic of peri-implantitis affects over 25% of dental implants. Current treatment depends on empirical patient and site-based stratifications and lacks a consistent risk grading system. We investigated a unique cohort of peri-implantitis patie...
Analysis of Tumor Microenvironment Characteristics in Bladder Cancer: Implications for Immune Checkpoint Inhibitor Therapy.
Frontiers in immunology
Apr 15, 2021
The tumor microenvironment (TME) plays a crucial role in cancer progression and recent evidence has clarified its clinical significance in predicting outcomes and efficacy. However, there are no studies on the systematic analysis of TME characteristi...
Hematologist-Level Classification of Mature B-Cell Neoplasm Using Deep Learning on Multiparameter Flow Cytometry Data.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Jun 9, 2020
The wealth of information captured by multiparameter flow cytometry (MFC) can be analyzed by recent methods of computer vision when represented as a single image file. We therefore transformed MFC raw data into a multicolor 2D image by a self-organiz...
The FluPRINT dataset, a multidimensional analysis of the influenza vaccine imprint on the immune system.
Scientific data
Oct 21, 2019
Machine learning has the potential to identify novel biological factors underlying successful antibody responses to influenza vaccines. The first attempts have revealed a high level of complexity in establishing influenza immunity, and many different...
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
Jul 7, 2019
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...
An ontology for representing hematologic malignancies: the cancer cell ontology.
BMC bioinformatics
Apr 25, 2019
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...
Machine learning identifies an immunological pattern associated with multiple juvenile idiopathic arthritis subtypes.
Annals of the rheumatic diseases
Mar 12, 2019
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...
Precision immunoprofiling by image analysis and artificial intelligence.
Virchows Archiv : an international journal of pathology
Nov 23, 2018
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, ...
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)
Nov 19, 2018
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)
Dec 6, 2014
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...
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