Match tier
Listed
Presence
Current · Arkansas
Last published
2023
Sources
OpenAlex · ORCID
Refreshed
2026-08-15
S
Saly Abouelenein
Researcher
Also affiliated: Advanced Animal Diagnostics (United States) (2018); Faculty of Public Health (2021); Arkansas Department of Agriculture (2021); Menoufia University (2018)
Unknown Researcher
4 h-index
9 pubs
53 cited
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Saly Abouelenein's research centers on the application of machine learning techniques to predict pharmacokinetic parameters for CFTR modulators, specifically elexacaftor-tezacaftor-ivacaftor. She investigates methods for predicting the average drug concentration (Cavg) using sparse sampling, evaluating the efficacy of single and multiple time points. Her work also includes modeling single variable-time measurements of these drugs in adults. Abouelenein has explored the relationship between insulin resistance and the spatial QRS-T angle in American adults, utilizing a case-control study approach. Additionally, she has examined occupational risk factors for pancreatic cancer in poultry plant workers, employing a random forest methodology.
Metrics
- h-index: 4
- Publications: 9
- Citations: 53
Selected Publications
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Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches (2025)
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Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches (2025)
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Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches (2025)
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P018 Single measurement quantification and modeling of elexafactor, tezacaftor and ivacaftor in adults: overlap between full and reduced dosing (2025)
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One- and Two-timepoint Sparse Sampling is Highly Predictive of Average Plasma Concentration of CFTR Modulators (2025)
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Elexacaftor-tezacaftor-ivacaftor pharmacokinetics with concurrent tacrolimus administration after lung transplant (2025)
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Abstract 16061: Correlation Between Obesity and Ventricular Tachycardia in Individuals With HFrEF: Analysis From the DERIVATE Cohort (2023)
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A case–control study of occupational risk factors for pancreatic cancer in poultry plant workers: a random forest approach (2021)
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Analysis of Professional Competencies for the Clinical Research Data Management Profession (2020)
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Metabolic syndrome and P-wave duration in the American population (2020)
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Biological Pathways of Long‐Term Visit‐to‐Visit Blood Pressure Variability in the American Population: Cardiovascular Health Study and Women’s Health Initiatives (2020)
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The Association between SNPs and a Quantitative Trait: Power Calculation (2018)
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The relation of blood lead and QRS-T angle in American adults (2018)
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Association Between Urinary Cadmium and QRS|T Angle Among Adults in the United States (2018)
Collaboration Network
Top Collaborators
Jennifer S. Guimbellot
University of Arkansas for Medical Sciences
5 shared publications
In database
- Elexacaftor-tezacaftor-ivacaftor pharmacokinetics with concurrent tacrolimus administration after lung transplant
- P018 Single measurement quantification and modeling of elexafactor, tezacaftor and ivacaftor in adults: overlap between full and reduced dosing
- Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches
- Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches
- Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches
A. Chalamalla
5 shared publications
In database
- Elexacaftor-tezacaftor-ivacaftor pharmacokinetics with concurrent tacrolimus administration after lung transplant
- One- and Two-timepoint Sparse Sampling is Highly Predictive of Average Plasma Concentration of CFTR Modulators
- Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches
- Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches
- Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches
Kathleen J. Ramos
University of Washington (US)
4 shared publications
- One- and Two-timepoint Sparse Sampling is Highly Predictive of Average Plasma Concentration of CFTR Modulators
- Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches
- Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches
- Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches
E.P. Costa
University of Alabama System (US)
2 shared publications
- Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches
- Predicting Cavg of CFTR Modulators Using Sparse Sampling: Evaluating Single and Multiple Time Points with Machine Learning Approaches
Mohammed F. Faramawi
Arkansas Department of Agriculture
1 shared publication
In database
- A case–control study of occupational risk factors for pancreatic cancer in poultry plant workers: a random forest approach
Eric S. Johnson
Arkansas Department of Health (US)
1 shared publication
- A case–control study of occupational risk factors for pancreatic cancer in poultry plant workers: a random forest approach
Jackson L Mosley
University of Arkansas for Medical Sciences
1 shared publication
In database
- Abstract 16061: Correlation Between Obesity and Ventricular Tachycardia in Individuals With HFrEF: Analysis From the DERIVATE Cohort
Dinesh Voruganti
University of Arkansas for Medical Sciences (US)
1 shared publication
- Abstract 16061: Correlation Between Obesity and Ventricular Tachycardia in Individuals With HFrEF: Analysis From the DERIVATE Cohort
Murrium I. Sadaf
University of Arkansas for Medical Sciences (US)
1 shared publication
- Abstract 16061: Correlation Between Obesity and Ventricular Tachycardia in Individuals With HFrEF: Analysis From the DERIVATE Cohort
Munthir Mansour
University of Arkansas for Medical Sciences
1 shared publication
In database
- Abstract 16061: Correlation Between Obesity and Ventricular Tachycardia in Individuals With HFrEF: Analysis From the DERIVATE Cohort
Robert Spraggins
University of Arkansas for Medical Sciences
1 shared publication
In database
- Abstract 16061: Correlation Between Obesity and Ventricular Tachycardia in Individuals With HFrEF: Analysis From the DERIVATE Cohort
Raffaele Abete
Fondazione Lanza (IT)
1 shared publication
- Abstract 16061: Correlation Between Obesity and Ventricular Tachycardia in Individuals With HFrEF: Analysis From the DERIVATE Cohort
Giovanni Donato Aquaro
Regione Toscana
1 shared publication
- Abstract 16061: Correlation Between Obesity and Ventricular Tachycardia in Individuals With HFrEF: Analysis From the DERIVATE Cohort
Andrea Baggiano
Centro Cardiologico Monzino (IT)
1 shared publication
- Abstract 16061: Correlation Between Obesity and Ventricular Tachycardia in Individuals With HFrEF: Analysis From the DERIVATE Cohort
Andrea Barison
Fondazione Toscana Gabriele Monasterio (IT)
1 shared publication
- Abstract 16061: Correlation Between Obesity and Ventricular Tachycardia in Individuals With HFrEF: Analysis From the DERIVATE Cohort
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