Publications by authors named "Aya M Awad"
Article Synopsis
- The study aimed to predict in-hospital mortality in patients with Acute Coronary Syndrome (ACS) using machine learning (ML) algorithms, specifically focusing on the QTc interval, and compared these predictions to established risk scores.
- Researchers analyzed data from 500 ACS patients over two years, developing three ML models: Random Forest, Naive Bayes, and PART, measuring their effectiveness against the GRACE and TIMI risk scores.
- The models showed promising performance, with the ML algorithms achieving an area under the curve (AUC) of 0.83 to 0.93, while the GRACE score had an AUC of 0.90, highlighting the potential of using ML for mortality prediction in hospital settings.
Lead (Pb(II)) contamination poses a significant threat to human health and the environment. This study investigates a new approach for Pb(II) removal from polluted water using copper terephthalic acid metal-organic framework/gum Arabic/potassium carrageenan (MGC) composite beads. We synthesized copper terephthalic acid MOF, potassium carrageenan beads, and MGC composite beads to evaluate their adsorption potential.
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