Publikationer av Adam Darwich
Refereegranskade
Artiklar
[1]
A. Boodaghian Asl et al., "A hybrid modeling approach to simulate complex systems and classify behaviors," NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS, vol. 13, no. 1, 2024.
[2]
L. Marzano et al., "Diagnosing an overcrowded emergency department from its Electronic Health Records," Scientific Reports, vol. 14, no. 1, 2024.
[3]
T. Haraldsson et al., "Exploring Hospital Overcrowding with an Explainable Time-to-Event Machine Learning Approach," Studies in Health Technology and Informatics, vol. 316, s. 678-682, 2024.
[4]
L. Marzano et al., "Exploring the discrepancies between clinical trials and real-world data: A small-cell lung cancer study," Clinical and Translational Science, vol. 17, no. 8, 2024.
[5]
S. F. Ling et al., "Population Pharmacokinetic Analysis and Simulation of Alternative Dosing Regimens for Biosimilars to Adalimumab and Etanercept in Patients with Rheumatoid Arthritis," Pharmaceutics, vol. 16, no. 6, s. 702-702, 2024.
[6]
L. Marzano et al., "Application of Process Mining for Modelling Small Cell Lung Cancer Prognosis," Studies in Health Technology and Informatics, vol. 302, s. 18-22, 2023.
[7]
A. S. Darwich et al., "Investigating the Connections Between Delivery of Care, Reablement, Workload, and Organizational Factors in Home Care Services : Mixed Methods Study," JMIR Human Factors, vol. 10, 2023.
[8]
E. El-Khateeb et al., "Using Prior Knowledge on Systems Through PBPK to Gain Further Insight into Routine Clinical Data on Trough Concentrations: The Case of Tacrolimus in Chronic Kidney Disease," Therapeutic Drug Monitoring, vol. 45, no. 6, s. 743-753, 2023.
[9]
L. Marzano et al., "A novel analytical framework for risk stratification of real‐world data using machine learning: A small cell lung cancer study," Clinical and Translational Science, vol. 15, no. 10, s. 2437-2447, 2022.
[10]
M. McAllister et al., "Developing Clinically Relevant Dissolution Specifications (CRDSs) for Oral Drug Products: Virtual Webinar Series," Pharmaceutics, vol. 14, no. 5, s. 1010-1010, 2022.
[11]
C. G. Wilson et al., "Integration of advanced methods and models to study drug absorption and related processes : An UNGAP perspective.," European Journal of Pharmaceutical Sciences, vol. 172, 2022.
[12]
N. Melillo och A. S. Darwich, "A latent variable approach to account for correlated inputs in global sensitivity analysis," Journal of Pharmacokinetics and Pharmacodynamics, 2021.
[13]
A. S. Darwich et al., "Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy," Annual Review of Pharmacology and Toxicology, vol. 61, no. 36, s. 1-21, 2021.
[14]
D. Scotcher et al., "Physiologically Based Pharmacokinetic Modeling of TransporterMediated Hepatic Disposition of Imaging Biomarker Gadoxetate in Rats," Molecular Pharmaceutics, vol. 18, no. 8, s. 2997-3009, 2021.
[15]
E. El-Katheeb et al., "Time to revisit Child-Pugh score as the basis for predicting drug clearance in hepatic impairment," Alimentary Pharmacology and Therapeutics, vol. 54, no. 4, s. 388-401, 2021.
[16]
H. Takita et al., "Application of the nested enzyme-within-enterocyte (NEWE) turnover model for predicting the time course of pharmacodynamic effects," CPT : Pharmacometrics and Systems Pharmacology (PSP), vol. 9, no. 11, s. 617-627, 2020.
[17]
E. Yau et al., "Global Sensitivity Analysis of the Rodgers and Rowland Model for Prediction of Tissue: Plasma Partitioning Coefficients: Assessment of the Key Physiological and Physicochemical Factors That Determine Small-Molecule Tissue Distribution," AAPS Journal, vol. 22, no. 2, s. 1-13, 2020.
[18]
A. Ahmad et al., "IMI – Oral biopharmaceutics tools project – Evaluation of bottom-up PBPK prediction success part 4 : Prediction accuracy and software comparisons with improved data and modelling strategies," European journal of pharmaceutics and biopharmaceutics, vol. 156, s. 50-63, 2020.
[19]
C. Zhang et al., "Serious Gaming of Logistics Management in Pediatric Emergency Medicine," INTERNATIONAL JOURNAL OF SERIOUS GAMES, vol. 7, no. 1, s. 47-77, 2020.
Konferensbidrag
[20]
M. N. Abourraja et al., "A Data-Driven Discrete Event Simulation Model to Improve Emergency Department Logistics," i Proceedings of the 2022 Winter Simulation Conference, 2022.
[21]
C. Orfanidis et al., "Monitoring neurological disorders with AI-enabled wearable systems," i DigiBiom 2022 : Proceedings of the 2022 Emerging Devices for Digital Biomarkers, 2022, s. 24-28.
[22]
A. Boodaghian Asl et al., "Simulation and Model Validation for Mental Health Factors Using a Multi-Methodology Hybrid Approach," i Proceedings - Winter Simulation Conference, 2021.
[23]
A. Boodaghian Asl et al., "Using pageRank and social network analysis to specify mental health factors," i Proceedings of the Design Society: 23rd International Conference on Engineering Design, ICED 2021,, 2021, s. 3379-3388.
Icke refereegranskade
Artiklar
[24]
L. Marzano et al., "A Comparative Analysis between Real-World Data and Clinical Trials to Evaluate Differences in Outcomes for SCLC Patients," Journal of Thoracic Oncology, vol. 18, no. 11, s. S697-S697, 2023.
[25]
E. Danell Lindström, A. S. Darwich och S. Meijer, "Towards a systems model to inform policy and interventions for medication adherence in chronic disease," International Journal of Clinical Pharmacy, vol. 43, no. 1, s. 293-293, 2021.
Kapitel i böcker
[26]
A. S. Darwich et al., "The Interplay Between Drug Release and Intestinal Gut-Wall Metabolism," i Oral Drug Delivery for Modified Release Formulations, Edmund S. Kostewicz, Maria Vertzoni, Heather A. E. Benson, Michael S. Roberts red., 1. uppl. : John Wiley & Sons, 2022, s. 65-86.
Senaste synkning med DiVA:
2024-11-21 00:30:01