Critical-care clinician and prospective PhD candidate in Respiratory Sciences. Building multimodal respiratory informatics for early prediction of COPD exacerbations and ICU deterioration in low-resource settings.
Over a decade across emergency medicine, prehospital systems, and intensive care, with a clinical focus on respiratory failure and critical-care decision-making.
I pair advanced bedside expertise with computational and data-driven methods — statistical modeling, foundations of machine learning, and Python-based clinical analysis — to build tools clinicians can actually use.
My prospective PhD targets multimodal respiratory informatics: integrating physiological signals, arterial blood gases, inflammatory biomarkers, imaging features, and respiratory audio to anticipate COPD exacerbations and ICU deterioration — closing a critical diagnostic gap in low-resource settings.
Thesis: Quasi-experimental study (n=102 ED nurses, 4 hospitals) evaluating a triage educational programme. Knowledge improved M=7.80 → 13.70 (t=−12.04, p<0.001, η²=0.59); skills M=105.65 → 155.6 (t=−12.9, p<0.001, η²=0.62). Advisor: Asst. Prof. Hekmat Al-Akash.
Thesis: Employees' triage of mass casualty incident situations. Advisor: Asst. Prof. Mahmoud Alwidyan.
Foundations in prehospital emergency response and field clinical care.
Multivariate regression identified monthly income (β=0.214, p=0.041) and communication method (β=0.219, p=0.035) as significant predictors of depression in mechanically ventilated patients.
Skills scores reached 100% post-intervention, with 85.5% retention at follow-up. Manuscript in preparation.
Mentored two MSc researchers in quantitative methodology, statistical analysis, and manuscript preparation under PI supervision.
Contributed to protocol development, simulation lab optimization, and competitive grant preparation; supported two manuscripts and conference outputs.
Integrating physiological signals, arterial blood gases, inflammatory biomarkers, imaging features, and respiratory audio data to enable early prediction of COPD exacerbations and ICU deterioration — targeting a critical diagnostic gap in low-resource settings.
Shawah'en, A., Alakash, H., Massadeh, R., Shajrawi, A., Maabreh, R., Assaf, E., & AlRabab'a, M. (2024). Triage knowledge level and skills among emergency nurses in Jordan: A quasi-experimental study.
Community Practitioner: the journal of the Community Practitioners' & Health Visitors' Association, 21, 83–101.
Shawahe'en, A., Alqwaqzea, D., Saifan, A. (2026). Cultural and Religious Influence in End-of-Life Decision-Making: A qualitative study.
Submitted Feb 2026.
Shawah'en, A. NextGen's tools for the future. Jordan (Haiku contribution). In National assessments in verse. Science, 2025, 390(6768), 22–23.
Paramedic Department · Prince Hussein Bin Abdullah II Academy of Civil Protection · Al-Balqa Applied University
3rd JUST International Conference, in collaboration with Monash University, Australia · 2017
SPSS 26 · Stata 17 · GraphPad Prism · R (tidyverse, ggplot2). Descriptive, inferential, regression, hypothesis testing.
MAXQDA · NVivo.
Intermediate: pandas, NumPy, scikit-learn. Audio/signal foundations for breath sounds, wheeze, crackles.
Advanced Life Support · Mechanical Ventilation · Simulation-Based Education · OSCE design.
Faculty of Nursing / Critical Care, Applied Science University
H_alakash@asu.edu.joFaculty of Nursing / Secretary General, Jordanian Nursing Council; Al-Hussein Bin Talal University
hnawafleh@ahu.edu.jo