A Cancer Biologist's Primer on Machine Learning Applications in High‐Dimensional Cytometry-Reference-Cited by-同舟云学术

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A Cancer Biologist's Primer on Machine Learning Applications in High‐Dimensional Cytometry

Published:2020-06-30 Issue:8 Volume:97 Page:782-799
ISSN:1552-4922
Container-title:Cytometry Part A
language:en
Short-container-title:Cytometry

Author:

Keyes Timothy J.¹²^ORCID,Domizi Pablo²,Lo Yu‐Chen²,Nolan Garry P.³,Davis Kara L.²

Affiliation:

1. Medical Scientist Training ProgramStanford University School of Medicine Stanford California

2. Department of PediatricsStanford University School of Medicine Stanford California

3. Department of Microbiology and Immunology | Baxter Laboratory for Stem Cell BiologyStanford University School of Medicine Stanford California

Funder

National Cancer Institute

National Institutes of Health

Publisher

Wiley

Subject

Cell Biology,Histology,Pathology and Forensic Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cyto.a.24158

Reference106 articles.

1. The History and Future of the Fluorescence Activated Cell Sorter and Flow Cytometry: A View from Stanford

2. Automated high-dimensional flow cytometric data analysis

3. Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum

4. Simultaneous epitope and transcriptome measurement in single cells

5. Applications of Mass Cytometry in Clinical Medicine

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1. A Revolution in Healthcare: AI-powered Cancer Imaging;Current Cancer Therapy Reviews;2024-08-13

2. State-of-the-art cytometry in the search of novel biomarkers in digestive cancers;Frontiers in Oncology;2024-05-29

3. A comparison of RNA-Seq data preprocessing pipelines for transcriptomic predictions across independent studies;BMC Bioinformatics;2024-05-08

4. An Explainable AI System for the Diagnosis of High-Dimensional Biomedical Data;BioMedInformatics;2024-01-11

5. Flow Cytometry: The Next Revolution;Cells;2023-07-17

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