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Durham University

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Mr Zakhriya Alhassan - all publications

  • 1: Alhassan, Zakhriya, Budgen, David, Alshammari, Riyad, Daghstani, Tahani, McGough, A. Stephen & Al Moubayed, Noura (2018), Stacked Denoising Autoencoders for Mortality Risk Prediction Using Imbalanced Clinical Data, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA). Orlando, FL, USA.
  • 2: Alhassan, Zakhriya, McGough, Stephen, Alshammari, Riyad, Daghstani, Tahini, Budgen, David & Al Moubayed, Noura (2018), Type-2 Diabetes Mellitus Diagnosis from Time Series Clinical Data using Deep Learning Models, in Kůrková, Věra, Manolopoulos, Yannis, Hammer, Barbara, Iliadis, Lazaros & Maglogiannis, Ilias eds, Lecture Notes in Computer Science 1141: International Conference on Artificial Neural Networks (ICANN). Rhodes, Greece, Springer, 468-478.
  • 3: Alessa, Ali, Faezipour, Miad & Alhassan, Zakhriya (2018), Text Classification of Flu-Related Tweets Using FastText with Sentiment and Keyword Features, 2018 IEEE International Conference on Healthcare Informatics (ICHI). New York, NY, USA.
  • Alhassan, Zakhriya, Budgen, David, Alshammari, Riyad & Moubayed, Noura Al (2020). Predicting Current Glycated Hemoglobin Levels in Adults From Electronic Health Records: Validation of Multiple Logistic Regression Algorithm. Journal of Medical Internet Research 8(7): e18963.
  • Alhassan, Zakhriya, Budgen, David, Alessa, Ali, Alshammari, Riyad, Daghstani, Tahini & Al Moubayed, Noura (2019), Collaborative Denoising Autoencoder for High Glycated Haemoglobin Prediction, in Tetko, Igor V. Kůrková, Věra Karpov, Pavel & Theis, Fabian eds, Lecture Notes in Computer Science 11731: 28th International Conference on Artificial Neural Networks, ICANN2019. Munich, Germany, Springer, Cham, 338-350.