Browsing Qatar University Annual Research Forum & Exhibition by Subject "Machine learning"

Now showing items 1-5 of 5

    • Artificial Intelligence in Predicting Heart Failure 

      Al-Mannai, Rashid Ebrahim; Almerekhi, Mohammed Hamad; Al-Mannai, Mohammed Abdulla; N, Mishahira; Sadasivuni, Kishor Kumar; ... more authors ( Qatar University Press , 2021 , Poster)
      Heart Failure is a major chronic disease that is increasing day by day and a great health burden in health care systems world wide. Artificial intelligence (AI) techniques such as machine learning (ML), deep learning (DL), ...

    • Blood biomarkers associated with autism spectrum disorder may provide early diagnosis 

      Rabbani, Naila; Thornalley, Paul John ( Qatar University Press , 2020 , Poster)
      Autism Spectrum Disorders (ASD) are a collection of neuropsychiatric disorders. ASD affects 1 in 87 in Qatar and is expected to increase. The high variability and heterogeneity of the symptoms makes diagnosis of ASD difficult ...

    • Blue-collar workers' travel behavior modeling using exPlainable machine learning model: The case of Qatar 

      Alkhereibi, Aya; AbuZaid, Ali; Wakjira, Tadesse ( Qatar University Press , 2021 , Poster)
      This paper presents a novel study on the examination of explainable machine learning (ML) technique to predict the mode choice for communities with a majority of blue-collared workers. A total of 4875 trip records for 1050 ...

    • Machine Learning Approach to Predict Metro Ridership based on Land Use Densities 

      Alkhereibi, Aya Hasan; Wakjira, Tadesse; kucukvar, Murat; Qidwai, Uvais; Muley, Deepti; ... more authors ( Qatar University Press , 2021 , Poster)
      Predicting metro ridership is an essential requirement for efficient metro operation and management. The dependence of metro ridership on the land use densities entails a need for an accurate predictive model. To this end, ...

    • Segmenting Liver Volume for Surgical Analysis 

      Al-Kababji, Ayman Jamal; Bensaali, Faycal; Dakua, Sarada Prasad ( Qatar University Press , 2021 , Poster)
      Introduction: Almost two million people worldwide die annually due to hepatic-related diseases. Half of these diseases are attributed to cirrhosis and the other half are related to hepatitis and hepatocellular carcinoma ...