Michael J. Reiter

Resilient Infrastructures via Digital Unification

Ang Chen, Sylvia Ratnasamy, Mohammad Reza Alizadeh, Mosharaf Chowdhury et autres

Digital transformation: A great science in the making.

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On the Importance of Local and Global Feature Learning for Automated Measurable Residual Disease Detection in Flow Cytometry Data

Lisa Weijler, Michael J. Reiter, Pedro Hermosilla, Margarita Maurer‐Granofszky et autres

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On the importance of local and global feature learning for automated measurable residual disease detection in flow cytometry data

Lisa Weijler, Michael J. Reiter, Pedro Hermosilla, Margarita Maurer‐Granofszky et autres

This paper evaluates various deep learning methods for measurable residual disease (MRD) detection in flow cytometry (FCM) data, addressing questions regarding the benefits of modeling long-range dependencies, methods of obtaining global information, and the importance of learning local features. Based on our …

Acoustic COVID-19 Detection Using Multiple Instance Learning

Michael J. Reiter, Franz Pernkopf

In the COVID-19 pandemic, a rigorous testing scheme was crucial. However, tests can be time-consuming and expensive. A machine learning-based diagnostic tool for audio recordings could enable widespread testing at low costs. In order to achieve comparability between such algorithms, the DiCOVA …

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EP.04A.06 A Comprehensive Lung Cancer Screening Program: Ten Years in Review

April Plank, Lisa Reagan, A. Dhamija, Denise Albano et autres

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Automated Immunophenotyping Assessment for Diagnosing Childhood Acute Leukemia using Set-Transformers

Elpiniki Maria Lygizou, Michael J. Reiter, Margarita Maurer‐Granofszky, Michael Norbert Dworzak et autres

Acute Leukemia is the most common hematologic malignancy in children and adolescents. A key methodology in the diagnostic evaluation of this malignancy is immunophenotyping based on Multiparameter Flow Cytometry (FCM). However, this approach is manual, and thus time-consuming and subjective. To alleviate …

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Automated Immunophenotyping Assessment for Diagnosing Childhood Acute Leukemia using Set-Transformers

Elpiniki Maria Lygizou, Michael J. Reiter, Margarita Maurer‐Granofszky, Michael Norbert Dworzak et autres

Acute Leukemia is the most common hematologic malignancy in children and adolescents. A key methodology in the diagnostic evaluation of this malignancy is immunophenotyping based on Multiparameter Flow Cytometry (FCM). However, this approach is manual, and thus time-consuming and subjective. To alleviate …

A polygenic risk score for the QT interval is an independent predictor of drug-induced QT prolongation

Steven T. Simon, Meng Lin, Katy E. Trinkley, Ryan G. Aleong et autres

Drug-induced QT prolongation (diLQTS), and subsequent risk of torsade de pointes, is a major concern with use of many medications, including for non-cardiac conditions. The possibility that genetic risk, in the form of polygenic risk scores (PGS), could be integrated into prediction …

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FATE: Feature-Agnostic Transformer-based Encoder for learning generalized embedding spaces in flow cytometry data

Lisa Weijler, Florian Kowarsch, Michael J. Reiter, Pedro Hermosilla et autres

While model architectures and training strategies have become more generic and flexible with respect to different data modalities over the past years, a persistent limitation lies in the assumption of fixed quantities and arrangements of input features. This limitation becomes particularly relevant …

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FATE: Feature-Agnostic Transformer-based Encoder for learning generalized embedding spaces in flow cytometry data

Lisa Weijler, Florian Kowarsch, Michael J. Reiter, Pedro Hermosilla et autres

While model architectures and training strategies have become more generic and flexible with respect to different data modalities over the past years, a persistent limitation lies in the assumption of fixed quantities and arrangements of input features. This limitation becomes particularly relevant …

FCM marker importance for MRD assessment in T‐cell acute lymphoblastic leukemia: An AIEOP‐BFM‐ALL‐FLOW study group report

Florian Kowarsch, Margarita Maurer‐Granofszky, Lisa Weijler, Matthias Wödlinger et autres

T-lineage acute lymphoblastic leukemia (T-ALL) accounts for about 15% of pediatric and about 25% of adult ALL cases. Minimal/measurable residual disease (MRD) assessed by flow cytometry (FCM) is an important prognostic indicator for risk stratification. In order to assess the MRD a …

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Author response for " FCM marker importance for MRD assessment in T‐Cell Acute Lymphoblastic Leukemia: An AIEOP‐BFM‐ALL‐FLOW Study Group Report"

Florian Kowarsch, Margarita Maurer‐Granofszky, Lisa Weijler, Matthias Wödlinger et autres