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Scientific Reports|April 2, 2025
Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniquesNegin Ashrafi, Armin Abdollahi, Kamiar Alaei, et al.
BMC Medical Informatics and Decision Making|August 8, 2024
Prediction of 30-day mortality for ICU patients with Sepsis-3Zhijiang Yu, Negin Ashrafi, Hexin Li, et al.
Frontiers in Artificial Intelligence|March 6, 2023
Rough-set based learning: Assessing patterns and predictability of anxiety, depression, and sleep scores associated with the use of cannabinoid-based medicine during COVID-19Sheela Ramanna, Negin Ashrafi, Evan Loster, et al.
IEEE Journal of Biomedical and Health Informatics|September 16, 2025
A Novel Multi-Task Teacher-Student Architecture with Self-Supervised Pretraining for 48-Hour Vasoactive-Inotropic Trend Analysis in Sepsis Mortality PredictionHouji Jin, Negin Ashrafi, Kamiar Alaei, et al.
Plos One|September 4, 2024
A machine learning-based prediction of hospital mortality in mechanically ventilated ICU patientsHexin Li, Negin Ashrafi, Chris Kang, et al.
BMC Medical Informatics and Decision Making|August 16, 2024
Prediction of sepsis mortality in ICU patients using machine learning methodsJiayi Gao, Yuying Lu, Negin Ashrafi, et al.
Materials (Basel, Switzerland)|September 18, 2020
Microstructural, Tribology and Corrosion Properties of Optimized Fe<sub>3</sub>O<sub>4</sub>-SiC Reinforced Aluminum Matrix Hybrid Nano Filler Composite Fabricated through Powder Metallurgy MethodNegin Ashrafi, M A Azmah Hanim, Masoud Sarraf, et al.
BMC Medical Informatics and Decision Making|July 24, 2025
Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patientsYong Si, Armin Abdollahi, Negin Ashrafi, et al.
Materials (Basel, Switzerland)|June 24, 2022
Magnetic, Electrical, and Physical Properties Evolution in Fe<sub>3</sub>O<sub>4</sub> Nanofiller Reinforced Aluminium Matrix Composite Produced by Powder Metallurgy MethodNegin Ashrafi, Azmah Hanim Mohamed Ariff, Dong-Won Jung, et al.
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