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ORCIDSai Veeranki
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- affiliation: Graz University of Technology, Institute of Neural Engineering, Austria
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2020 – today
- 2024
[c17]Diether Kramer, Stefanie Jauk, Sai Veeranki, Michael Schrempf, Julia Traub, Eva Kugel, Anna Prisching, Sandra Domnanich, Maria Leopold, Peter Krisper, Gerald Sendlhofer:
Machine Learning-Based Prediction of Malnutrition in Surgical In-Patients: A Validation Pilot Study. dHealth 2024: 156-157- 2023
- [j3]Martin Baumgartner
, Sai Pavan Kumar Veeranki, Dieter Hayn, Günter Schreier:
Introduction and Comparison of Novel Decentral Learning Schemes with Multiple Data Pools for Privacy-Preserving ECG Classification. J. Heal. Informatics Res. 7(3): 291-312 (2023) - [j2]Manuel Lentzen, Thomas Linden, Sai Veeranki, Sumit Madan, Diether Kramer, Werner Leodolter, Holger Fröhlich:
A Transformer-Based Model Trained on Large Scale Claims Data for Prediction of Severe COVID-19 Disease Progression. IEEE J. Biomed. Health Informatics 27(9): 4548-4558 (2023) - [c16]Julian Gutheil, Philip Stampfer, Diether Kramer, Manuel Wechselberger, Sai Pavan Kumar Veeranki, Michael Schrempf, Peter Mrak, Martina Aubel, Franz Feichtner:
Frail People in LABLand: Development of an Easy-to-Use Machine Learning Model to Identify Frail People in Hospitals Based on Laboratory Data. dHealth 2023: 212-219 - 2022
- [c15]Stefanie Jauk, Sai Pavan Kumar Veeranki, Diether Kramer, Stefan Högler, David Mühlecker, Erwin Eberhartl, Arthur Schueler, Christian Chvosta, Wolfgang Strasser, Reinhold Strasser, Werner Leodolter:
External Validation of a Machine Learning Based Delirium Prediction Software in Clinical Routine. dHealth 2022: 93-100 - [c14]Michael Schrempf, Seda Polat Erdeniz, Diether Kramer, Stefanie Jauk, Sai Pavan Kumar Veeranki, Werner Ribitsch, Werner Leodolter, Peter P. Rainer:
Development of an Architecture to Implement Machine Learning Based Risk Prediction in Clinical Routine: A Service-Oriented Approach. dHealth 2022: 262-269 - 2021
- [c13]Martin Baumgartner, Martin Kropf, Lukas Haider, Sai Veeranki, Dieter Hayn, Günter Schreier:
ECG Classification Combining Conventional Signal Analysis, Random Forests and Neural Networks - a Stacked Learning Scheme. CinC 2021: 1-4 - [c12]Michael Schrempf, Diether Kramer, Stefanie Jauk, Sai Pavan Kumar Veeranki, Werner Leodolter, Peter P. Rainer:
Machine Learning Based Risk Prediction for Major Adverse Cardiovascular Events. dHealth 2021: 136-143 - [c11]Hans Moen, Dari AlHuwail, Jari Björne, Lori Block, Sven Celin, Eunjoo Jeon, Karl Kreiner, James Mitchell, Gabriela Ozegovic, Charlene Esteban Ronquillo, Lydia Sequeira, Jude L. Tayaben, Maxim Topaz, Sai Pavan Kumar Veeranki, Laura-Maria Peltonen:
Towards Automated Screening of Literature on Artificial Intelligence in Nursing. MedInfo 2021: 637-640
2010 – 2019
- 2019
- [c10]Stefanie Jauk, Diether Kramer, Franz Quehenberger, Sai Pavan Kumar Veeranki, Dieter Hayn, Günter Schreier, Werner Leodolter:
Information Adapted Machine Learning Models for Prediction in Clinical Workflow. dHealth 2019: 65-72 - [c9]Sai Pavan Kumar Veeranki, Diether Kramer, Dieter Hayn, Stefanie Jauk, Alphons Eggerth, Franz Quehenberger, Werner Leodolter, Günter Schreier:
Is Regular Re-Training of a Predictive Delirium Model Necessary After Deployment in Routine Care? dHealth 2019: 186-191 - [c8]Alphons Eggerth, Dieter Hayn, Karl Kreiner, Sai Veeranki, Heimo Traninger, Robert Modre-Osprian, Günter Schreier:
Patient Record Linkage for Data Quality Assessment Based on Time Series Matching. dHealth 2019: 210-217 - [c7]Michael Sams, Alphons Eggerth, Dieter Hayn, Sai Veeranki, Günter Schreier:
Predictive Modelling and Its Visualization for Telehealth Data - Concept and Implementation of an Interactive Viewer. dHealth 2019: 234-241 - [c6]Sai Pavan Kumar Veeranki, Dieter Hayn, Stefanie Jauk, Franz Quehenberger, Diether Kramer, Werner Leodolter, Günter Schreier:
An Improvised Classification Model for Predicting Delirium. MedInfo 2019: 1566-1567 - 2018
- [j1]Dieter Hayn, Sai Veeranki, Martin Kropf, Alphons Eggerth, Karl Kreiner, Diether Kramer, Günter Schreier:
Predictive analytics for data driven decision support in health and care. it Inf. Technol. 60(4): 183-194 (2018) - [c5]Alphons Eggerth, Dieter Hayn, Sai Veeranki, Jörg Stieg, Günter Schreier:
Utilising Information of the Case Fee Catalogue to Enhance 30-Day Readmission Prediction in the German DRG System. EFMI-STC 2018: 40-44 - [c4]Sai Pavan Kumar Veeranki, Dieter Hayn, Diether Kramer, Stefanie Jauk, Günter Schreier:
Effect of Nursing Assessment on Predictive Delirium Models in Hospitalised Patients. eHealth 2018: 124-131 - [c3]Alphons Eggerth, Dieter Hayn, Sai Veeranki, Jörg Stieg, Günter Schreier:
Prediction of Readmissions in the German DRG System Based on §21 Datasets. GMDS 2018: 170-174 - [c2]Sai Veeranki, Dieter Hayn, Alphons Eggerth, Stefanie Jauk, Diether Kramer, Werner Leodolter, Günter Schreier:
On the Representation of Machine Learning Results for Delirium Prediction in a Hospital Information System in Routine Care. ICIMTH 2018: 97-100 - 2017
- [c1]Diether Kramer, Sai Veeranki, Dieter Hayn, Franz Quehenberger, Werner Leodolter, Christian Jagsch, Günter Schreier:
Development and Validation of a Multivariable Prediction Model for the Occurrence of Delirium in Hospitalized Gerontopsychiatry and Internal Medicine Patients. eHealth 2017: 32-39
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