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Andreas Schuppert

Explore the profile of Andreas Schuppert including associated specialties, affiliations and a list of published articles. Areas
Snapshot
Articles 59
Citations 851
Followers 0
Related Specialties
Science
General Medicine
Molecular Biology
Top 10 Co-Authors
Gernot Marx
Johannes Bickenbach
Lars Kuepfer
Sebastian Johannes Fritsch
Morris Riedel
Konstantin Sharafutdinov
Michael Lenz
Tim H Brummendorf
Christian Karagiannidis
Moein E Samadi
Published In
Sci Rep
PLoS One
Diagnostics (Basel)
Hum Mol Genet
Med Klin Intensivmed Notfmed
Affiliations
Soon will be listed here.
Recent Articles
1.
Monitoring individualized glucose levels predicts risk for bradycardia in type 2 diabetes patients with chronic kidney disease: a pilot study
Farhadi Ghalati P, E Samadi M, Verket M, Balfanz P, Muller-Wieland D, Jonas S, et al.
Sci Rep . 2024 Dec; 14(1):30290. PMID: 39638855
Patients with diabetes mellitus (DM) and chronic kidney disease (CKD) exhibit an elevated risk for cardiac arrhythmias, such as bradycardia, which may potentially lead to sudden cardiac death (SCD). While...
2.
Spike by spike frequency analysis of amperometry traces provides statistical validation of observations in the time domain
Krishnan J, Lian Z, Oomen P, Amir-Aref M, He X, Majdi S, et al.
Sci Rep . 2024 Oct; 14(1):25142. PMID: 39448745
Amperometry is a commonly used electrochemical method for studying the process of exocytosis in real-time. Given the high precision of recording that amperometry procedures offer, the volume of data generated...
3.
Computational Simulation of Virtual Patients Reduces Dataset Bias and Improves Machine Learning-Based Detection of ARDS from Noisy Heterogeneous ICU Datasets
Sharafutdinov K, Fritsch S, Iravani M, Farhadi Ghalati P, Saffaran S, Bates D, et al.
IEEE Open J Eng Med Biol . 2024 Aug; 5:611-620. PMID: 39184970
Machine learning (ML) technologies that leverage large-scale patient data are promising tools predicting disease evolution in individual patients. However, the limited generalizability of ML models developed on single-center datasets, and...
4.
Authors' response: "Development of a machine learning model for prediction of the duration of unassisted spontaneous breathing in patients during prolonged weaning from mechanical ventilation"
Fritsch S, Riedel M, Marx G, Bickenbach J, Schuppert A
J Crit Care . 2024 Jun; 83:154850. PMID: 38906778
No abstract available.
5.
Noisecut: a python package for noise-tolerant classification of binary data using prior knowledge integration and max-cut solutions
E Samadi M, Mirzaieazar H, Mitsos A, Schuppert A
BMC Bioinformatics . 2024 Apr; 25(1):155. PMID: 38641616
Background: Classification of binary data arises naturally in many clinical applications, such as patient risk stratification through ICD codes. One of the key practical challenges in data classification using machine...
6.
Epigenetic and Transcriptional Shifts in Human Neural Stem Cells after Reprogramming into Induced Pluripotent Stem Cells and Subsequent Redifferentiation
Haubenreich C, Lenz M, Schuppert A, Peitz M, Koch P, Zenke M, et al.
Int J Mol Sci . 2024 Mar; 25(6). PMID: 38542188
Induced pluripotent stem cells (iPSCs) and their derivatives have been described to display epigenetic memory of their founder cells, as well as de novo reprogramming-associated alterations. In order to selectively...
7.
Development of a machine learning model for prediction of the duration of unassisted spontaneous breathing in patients during prolonged weaning from mechanical ventilation
Fritsch S, Riedel M, Marx G, Bickenbach J, Schuppert A
J Crit Care . 2024 Mar; 82:154795. PMID: 38531748
Purpose: Treatment of patients undergoing prolonged weaning from mechanical ventilation includes repeated spontaneous breathing trials (SBTs) without respiratory support, whose duration must be balanced critically to prevent over- and underload...
8.
A hybrid modeling framework for generalizable and interpretable predictions of ICU mortality across multiple hospitals
E Samadi M, Guzman-Maldonado J, Nikulina K, Mirzaieazar H, Sharafutdinov K, Fritsch S, et al.
Sci Rep . 2024 Mar; 14(1):5725. PMID: 38459085
The development of reliable mortality risk stratification models is an active research area in computational healthcare. Mortality risk stratification provides a standard to assist physicians in evaluating a patient's condition...
9.
Redefining pandemic preparedness: Multidisciplinary insights from the CERP modelling workshop in infectious diseases, workshop report
Nunes M, Thommes E, Frohlich H, Flahault A, Arino J, Baguelin M, et al.
Infect Dis Model . 2024 Mar; 9(2):501-518. PMID: 38445252
In July 2023, the Center of Excellence in Respiratory Pathogens organized a two-day workshop on infectious diseases modelling and the lessons learnt from the Covid-19 pandemic. This report summarizes the...
10.
Developing an Artificial Intelligence-Based Representation of a Virtual Patient Model for Real-Time Diagnosis of Acute Respiratory Distress Syndrome
Barakat C, Sharafutdinov K, Busch J, Saffaran S, Bates D, Hardman J, et al.
Diagnostics (Basel) . 2023 Jun; 13(12). PMID: 37370993
Acute Respiratory Distress Syndrome (ARDS) is a condition that endangers the lives of many Intensive Care Unit patients through gradual reduction of lung function. Due to its heterogeneity, this condition...