Ekaterina Koledova

Orcid: 0000-0003-2572-9052

According to our database1, Ekaterina Koledova authored at least 10 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Preferences for Injection Device Settings and the Association with Adherence to Growth Hormone Treatment in Patient with Growth Disorders.
Proceedings of the Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024

2023
Participatory Study to Explore Healthcare Professionals' Perceptions of a Connected Digital Solution for Adherence Monitoring of Recombinant Human Growth Hormone Treatment: Study Protocol and First Findings.
Proceedings of the Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023, Gothenburg, Sweden, 22, 2023

2022
Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10, 929 children using a connected auto-injector device.
BMC Medical Informatics Decis. Mak., 2022

Observed High Adherence to Recombinant Human Growth Hormone Treatment Using a Multi-Component Approach to Improve Adherence in Individuals with Growth Disorders.
Proceedings of the Challenges of Trustable AI and Added-Value on Health, 2022

2021
Connected health for growth hormone treatment research and clinical practice: learnings from different sources of real-world evidence (RWE) - large electronically collected datasets, surveillance studies and individual patients' cases.
BMC Medical Informatics Decis. Mak., 2021

High Engagement of Patients Monitored by a Digital Health Ecosystem Indicates Significant Improvements of Key r-hGH Treatment Metrics.
Proceedings of the Public Health and Informatics, 2021

Digital Health in the Management of Pediatric Growth Hormone Therapy - 10 Years of Developments.
Proceedings of the Public Health and Informatics, 2021

Using Deep Learning for Individual-Level Predictions of Adherence with Growth Hormone Therapy.
Proceedings of the Public Health and Informatics, 2021

A Data-Driven Intervention Framework for Improving Adherence to Growth Hormone Therapy Based on Clustering Analysis and Traffic Light Alerting Systems.
Proceedings of the Applying the FAIR Principles to Accelerate Health Research in Europe in the Post COVID-19 Era, 2021

2020
Analysis of real-world data on growth hormone therapy adherence using a connected injection device.
BMC Medical Informatics Decis. Mak., 2020


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