Projects per year
Personal profile
Research profile
Research focuses on the use and integration of advanced technologies, such as artificial intelligence (AI) and machine learning (ML), to improve the diagnosis and treatment of diabetes and other chronic conditions. I am particularly interested in leveraging these tools to develop more personalized healthcare solutions.
Teaching profile
My approach to teaching and supervision is rooted in the principles of problem-based learning (PBL) and group-organized project work. I believe that this active learning method enhances students' ability to take responsibility for their own learning, promotes critical thinking and problem-solving skills, and encourages collaboration and communication.
In my pedagogical activities, I focus on creating relevant and authentic learning experiences, where students can apply their theoretical knowledge in practical contexts. I often integrate case studies, real-life project assignments, data from clinical studies, and external collaborators that reflect real challenges. In this way, I strive to motivate and engage students while providing them with the opportunity to develop the skills and competencies relevant to their future careers in the healthcare sector.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
University pedagogics for asisstant lecturers
Award Date: 1 Dec 2018
PhD, Predictive models in diabetes
Award Date: 8 Sept 2016
M.Sc. BME
Award Date: 11 Jun 2011
External positions
Editor, ScienceBank
2025 → …
Member of Editorial Board, Journal of Diabetes Science and Technology
2024 → …
Keywords
- Biomedical Engineering
- Problem Based Learning
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Collaborations from the last five years
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The use of continuous glucose monitoring (CGM) devices for advanced diagnostics and diabetes care
Cichosz, S. L. (PI)
01/10/2022 → 01/10/2026
Project: Research
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Sten-O Starter Kliniske Effekter
Cichosz, S. L. (PI), Bender, C. (PI), Jensen, M. H. (PI) & Hejlesen, O. (PI)
01/09/2020 → 31/12/2023
Project: Research
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DiaData – et IT-ekspertsystem til optimering af behandling af type-2 diabetes
Cichosz, S. L. (PI)
01/01/2013 → 01/12/2013
Project: Research
Research output
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Artificial Intelligence to Diagnose Complications of Diabetes
Ayers, A. T., Ho, C. N., Kerr, D., Cichosz, S. L., Mathioudakis, N., Wang, M., Najafi, B., Moon, S.-J., Pandey, A. & Klonoff, D. C., Jan 2025, In: Journal of Diabetes Science and Technology. 19, 1, p. 246-264 19 p.Research output: Contribution to journal › Journal article › Research › peer-review
4 Citations (Scopus) -
From Stability to Variability: Classification of Healthy Individuals, Prediabetes, and Type 2 Diabetes using Glycemic Variability Indices from Continuous Glucose Monitoring Data
Cichosz, S. L., Kronborg, T., Laugesen, E., Hangaard, S., Fleischer, J., Hansen, T. K., Jensen, M. H., Poulsen, P. L. & Vestergaard, P., 8 Jan 2025, In: Diabetes Technology & Therapeutics. 27, 1, p. 34-44 11 p.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile11 Citations (Scopus)66 Downloads (Pure) -
Explainable Machine Learning Models to Predict Weekly Risk of Hyperglycemia, Hypoglycemia and Glycemic Variability in Patients with Type 1 Diabetes Based on Continuous Glucose Monitoring
Cichosz, S. L., Olesen, S. S. & Jensen, M. H., 8 Oct 2024, (E-pub ahead of print) In: Journal of Diabetes Science and Technology.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile5 Citations (Scopus)23 Downloads (Pure) -
Prediction of pancreatic cancer risk in patients with new-onset diabetes using a machine learning approach based on routine biochemical parameters
Cichosz, S. L., Jensen, M. H., Hejlesen, O., Henriksen, S. D., Drewes, A. M. & Olesen, S. S., Feb 2024, In: Computer Methods and Programs in Biomedicine. 244, 107965.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile11 Citations (Scopus)95 Downloads (Pure) -
Artificial intelligence in nursing: driving a new standard in patient care
Bender, C., Pessoto Hirata, R., Kronborg, T. & Cichosz, S. L., 12 May 2025, In: Texto & Contexto Enfermagem. 34, e2025E001.Research output: Contribution to journal › Editorial
Datasets
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Synthetic Continuous Glucose Monitoring (CGM) Signals
Cichosz, S. L. (Creator) & Xylander, A. A. P. (Creator), Mendeley Data, Apr 2021
DOI: 10.17632/chd8hx65r4.1, http://dx.doi.org/10.17632/chd8hx65r4.1
Dataset
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Classification of Gastroparesis from Glycemic Variability in Type 1 Diabetes: A Proof-of-Concept Study
Cichosz, S. L. (Creator) & Hejlesen, O. (Creator), Sage Journals, 2021
DOI: 10.25384/sage.c.5425946, https://sage.figshare.com/collections/Classification_of_Gastroparesis_from_Glycemic_Variability_in_Type_1_Diabetes_A_Proof-of-Concept_Study/5425946
Dataset
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sj-pdf-1-dst-10.1177_19322968211015206 – Supplemental material for Classification of Gastroparesis from Glycemic Variability in Type 1 Diabetes: A Proof-of-Concept Study
Cichosz, S. L. (Creator) & Hejlesen, O. (Creator), Sage Journals, 2021
DOI: 10.25384/sage.14602838.v1, https://doi.org/10.25384%2Fsage.14602838.v1
Dataset: Supplementary material
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Supplement – Supplemental material for Precise Prediction of Total Body Lean and Fat Mass From Anthropometric and Demographic Data: Development and Validation of Neural Network Models
Cichosz, S. L. (Creator), Rasmussen, N. H. (Creator), Vestergaard, P. (Creator) & Hejlesen, O. (Creator), Sage Journals, 2020
DOI: 10.25384/sage.13246893.v1, https://doi.org/10.25384%2Fsage.13246893.v1
Dataset: Supplementary material
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Precise Prediction of Total Body Lean and Fat Mass From Anthropometric and Demographic Data: Development and Validation of Neural Network Models
Cichosz, S. L. (Creator), Rasmussen, N. H. (Creator), Vestergaard, P. (Creator) & Hejlesen, O. (Creator), Sage Journals, 2020
DOI: 10.25384/sage.c.5209971, https://sage.figshare.com/collections/Precise_Prediction_of_Total_Body_Lean_and_Fat_Mass_From_Anthropometric_and_Demographic_Data_Development_and_Validation_of_Neural_Network_Models/5209971
Dataset
Activities
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Journal of Diabetes Science and Technology (JDST), Editorial Board Member (EBM)
Cichosz, S. L. (Other)
2024 → …Activity: Other
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The Swiss Data Science Center, SDSC, Schweiz, funding application review
Cichosz, S. L. (Consultant)
Dec 2024Activity: Public/private sector consultancy and other employment › Public Sector Consultancy
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Journal of Diabetes Science and Technology (Journal)
Cichosz, S. L. (Peer reviewer)
13 Jun 2025Activity: Editorial work and peer review › Peer review of manuscripts › Research
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Journal of Diabetes and its Complications (Journal)
Cichosz, S. L. (Peer reviewer)
May 2025Activity: Editorial work and peer review › Peer review of manuscripts › Research
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Diabetes Technology & Therapeutics (Journal)
Cichosz, S. L. (Peer reviewer)
May 2025Activity: Editorial work and peer review › Peer review of manuscripts › Research