Frederik Christensen
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Frederik Christensen has a total of 21 co-authors. Here are the top co-authors by number of shared publications:
- Deniz Kenan Kılıç
Department of Materials and Production, Aalborg University, 9220 Aalborg, Denmark
4 shared publications - Izabela Nielsen
Aalborg University
4 shared publications - Alexander Djupnes Fuglkjær
Department of Materials and Production Aalborg University Aalborg Denmark
3 shared publications - Tarec Christoffer El-Galaly
Aarhus University Hospital, Aarhus, Denmark
3 shared publications - Andreas Glenthøj
Danish Red Blood Cell Center, Department of Hematology, Copenhagen University Hospital – Rigshospitalet, Copenhagen, Denmark
2 shared publications - Henrik Frederiksen
Department of Hematology, Odense University Hospital, Odense, Denmark
2 shared publications
Latest Publications
- Open Access
Use of Scores in Risk Stratification of Febrile Neutropenia—A Scoping Review
Purpose: A scoping review of the published risk stratification scores for febrile neutropenia (FN) was performed to provide a basis for further research and optimization of risk stratification models that can support evidence-based clinical decision-making with a combined individual patient and health resource perspective. Methods: The scoping review utilized the Preferred Reporting Items for Systematic Reviews and Meta-analysis extension for Scoping Reviews (PRISMA-ScR). Studies reporting risk stratification models for FN and published in the PubMed and/or Scopus databases between 2000 and 2024 were retrieved and reviewed. Study eligibility criteria were adult cancer patients and articles utilizing FN risk stratification methods. Two researchers reviewed all relevant studies separately to determine if they were eligible for inclusion and extracted the necessary data. Results: A total of 210 papers was screened by title and A further 158 were screened by retrieval and eligibility, and 14 studies were found eligible after reviewing full papers. Studies have different cohort sizes (min 31, max 4434), age and gender distributions, cancer types (1 hematological, 3 gynecological, 10 mixtures of hematological and solid cancers), definitions of FN and complication, study type (2 retrospective, 12 prospective). The resulting papers mostly focused on validating CISNE and MASCC scores. Additionally, they investigated possible improvements by evaluating revised versions of the MASCC score. Conclusions: The scoping review revealed inconsistencies in key definitions when using risk stratification scores. It is concluded that the field could benefit from more consensus in definitions and research approaches to secure the generalizability and utility of the research.
Open AccessUse of Scores in Risk Stratification of Febrile Neutropenia—A Scoping Review
Purpose: A scoping review of the published risk stratification scores for febrile neutropenia (FN) was performed to provide a basis for further research and optimization of risk stratification models that can support evidence-based clinical decision-making with a combined individual patient and health resource perspective. Methods: The scoping review utilized the Preferred Reporting Items for Systematic Reviews and Meta-analysis extension for Scoping Reviews (PRISMA-ScR). Studies reporting risk stratification models for FN and published in the PubMed and/or Scopus databases between 2000 and 2024 were retrieved and reviewed. Study eligibility criteria were adult cancer patients and articles utilizing FN risk stratification methods. Two researchers reviewed all relevant studies separately to determine if they were eligible for inclusion and extracted the necessary data. Results: A total of 210 papers was screened by title and A further 158 were screened by retrieval and eligibility, and 14 studies were found eligible after reviewing full papers. Studies have different cohort sizes (min 31, max 4434), age and gender distributions, cancer types (1 hematological, 3 gynecological, 10 mixtures of hematological and solid cancers), definitions of FN and complication, study type (2 retrospective, 12 prospective). The resulting papers mostly focused on validating CISNE and MASCC scores. Additionally, they investigated possible improvements by evaluating revised versions of the MASCC score. Conclusions: The scoping review revealed inconsistencies in key definitions when using risk stratification scores. It is concluded that the field could benefit from more consensus in definitions and research approaches to secure the generalizability and utility of the research.
- Open Access
A Simulation and TOPSIS Approach to the Satellite Constellation Design Problem
The design of satellite constellations is a complex optimization problem interdependent with other decision problems and multiple competing, user-specific criteria. Consequently, it is very difficult to make a final decision on the constellation design. This study proposes a full simulation and evaluation framework for designing a satellite constellation. Firstly, constructing a solution space by constraining orbital parameters and varying satellite count and plane configuration. Secondly, employing six evaluation metrics—covering both cost and coverage—that are weighted via the case company, Sternula’s setting, with the TOPSIS approach for ranking the candidate constellations. A subsequent sensitivity analysis evaluates robustness to shifts in criterion weights and per-satellite cost. The study indicates that a Walker Star constellation with 97.5° inclination, 105 satellites in 15 planes (phasing 7) achieves the best cost–coverage balance for the case company and remains stable under weight and cost variations.
Open AccessA Simulation and TOPSIS Approach to the Satellite Constellation Design Problem
The design of satellite constellations is a complex optimization problem interdependent with other decision problems and multiple competing, user-specific criteria. Consequently, it is very difficult to make a final decision on the constellation design. This study proposes a full simulation and evaluation framework for designing a satellite constellation. Firstly, constructing a solution space by constraining orbital parameters and varying satellite count and plane configuration. Secondly, employing six evaluation metrics—covering both cost and coverage—that are weighted via the case company, Sternula’s setting, with the TOPSIS approach for ranking the candidate constellations. A subsequent sensitivity analysis evaluates robustness to shifts in criterion weights and per-satellite cost. The study indicates that a Walker Star constellation with 97.5° inclination, 105 satellites in 15 planes (phasing 7) achieves the best cost–coverage balance for the case company and remains stable under weight and cost variations.
- 16 February 2026
- Published by Wiley in American Journal of Hematology
- Vol. 101 (5) , 1134-1140
Acquired Hemolytic Anemia Is Associated With Higher Risk of Symptomatic Gallstone Disease
- 16 February 2026
- Published by Wiley in American Journal of Hematology
- Vol. 101 (5) , 1134-1140
Acquired Hemolytic Anemia Is Associated With Higher Risk of Symptomatic Gallstone Disease
- Open Access
Machine Learning‐Based Detection of HbS and HbC Carriers in the UK General Population
Background: Haemoglobin S (HbS) and C (HbC) are the most important sickling variants on the African continent, imposing major health burdens. Early detection of carrier status is crucial but often hindered by resource limitations. Objectives: To develop machine learning (ML) models to accurately classify HbS and HbC carriers using readily available routine blood tests, facilitating cost‐effective mass screening. Methods: We utilised demographic and routine blood parameters from 469,248 individuals from the UK general population, including 1635 individuals with HbS and/or HbC variants identified by whole exome sequencing, to develop ML models for carrier detection based on standard blood tests. Three ML models (Logistic Regression [LR], Random Forest [RF] and XGBoost [XGB]) were trained using 32 different standard blood test results. Results: All models demonstrated high discriminatory ability (ROC‐AUC: LR 0.951; RF 0.943; XGB 0.956) in the UK general population. At a sensitivity of 95%, specificities were 77% (LR), 76% (RF) and 78% (XGB). SHAP analysis revealed consistent key features across models. When use was restricted to black individuals, performance fell considerably. Conclusions: ML models based on routine blood tests effectively identify HbS and HbC carriers in a mixed general population. This approach has the potential to enhance screening efficiency by reducing reliance on specialised techniques.
Open AccessMachine Learning‐Based Detection of HbS and HbC Carriers in the UK General Population
Background: Haemoglobin S (HbS) and C (HbC) are the most important sickling variants on the African continent, imposing major health burdens. Early detection of carrier status is crucial but often hindered by resource limitations. Objectives: To develop machine learning (ML) models to accurately classify HbS and HbC carriers using readily available routine blood tests, facilitating cost‐effective mass screening. Methods: We utilised demographic and routine blood parameters from 469,248 individuals from the UK general population, including 1635 individuals with HbS and/or HbC variants identified by whole exome sequencing, to develop ML models for carrier detection based on standard blood tests. Three ML models (Logistic Regression [LR], Random Forest [RF] and XGBoost [XGB]) were trained using 32 different standard blood test results. Results: All models demonstrated high discriminatory ability (ROC‐AUC: LR 0.951; RF 0.943; XGB 0.956) in the UK general population. At a sensitivity of 95%, specificities were 77% (LR), 76% (RF) and 78% (XGB). SHAP analysis revealed consistent key features across models. When use was restricted to black individuals, performance fell considerably. Conclusions: ML models based on routine blood tests effectively identify HbS and HbC carriers in a mixed general population. This approach has the potential to enhance screening efficiency by reducing reliance on specialised techniques.
- Open Access
- 6 January 2025
- Published by Elsevier in Computer Methods and Programs in Biomedicine
- Vol. 260, 108581
Classification of -thalassemia data using machine learning models- 6 January 2025
- Published by Elsevier in Computer Methods and Programs in Biomedicine
- Vol. 260, 108581
Open AccessClassification of -thalassemia data using machine learning models