Knowledge transfer to enhance the performance of deep learning models for automated classification of B cell neoplasms

Mallesh N, Zhao M, Meintker L, Hoellein A, Elsner F, Lueling H, Haferlach T, Kern W, Westermann J, Brossart P, Krause S, Krawitz PM (2021)

Publication Type: Journal article

Publication year: 2021

Journal

Patterns Cell Press

Book Volume: 2

Journal Issue: 10

DOI: 10.1016/j.patter.2021.100351

Abstract

Multi-parameter flow cytometry (MFC) is a cornerstone in clinical decision making for leukemia and lymphoma. MFC data analysis requires manual gating of cell populations, which is time-consuming, subjective, and often limited to a two-dimensional space. In recent years, deep learning models have been successfully used to analyze data in high-dimensional space and are highly accurate. However, AI models used for disease classification with MFC data are limited to the panel they were trained on. Thus, a key challenge in deploying AI into routine diagnostics is the robustness and adaptability of such models. This study demonstrates how transfer learning can be applied to boost the performance of models with smaller datasets acquired with different MFC panels. We trained models for four additional datasets by transferring the features learned from our base model. Our workflow increased the model's overall performance and, more prominently, improved the learning rate for small training sizes.

Authors with CRIS profile

Lisa Meintker Department of Medicine 5 – Haematology and Oncology Stefan Krause Department of Medicine 5 – Haematology and Oncology

Involved external institutions

Rheinische Friedrich-Wilhelms-Universität Bonn DE Germany (DE) Charité - Universitätsmedizin Berlin DE Germany (DE) MLL Münchner Leukämielabor GmbH DE Germany (DE) Universitätsklinikum Bonn DE Germany (DE) res mechanica GmbH DE Germany (DE)

How to cite

APA:

Mallesh, N., Zhao, M., Meintker, L., Hoellein, A., Elsner, F., Lueling, H.,... Krawitz, P.M. (2021). Knowledge transfer to enhance the performance of deep learning models for automated classification of B cell neoplasms. Patterns, 2(10). https://doi.org/10.1016/j.patter.2021.100351

MLA:

Mallesh, Nanditha, et al. "Knowledge transfer to enhance the performance of deep learning models for automated classification of B cell neoplasms." Patterns 2.10 (2021).

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