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… Research Institute The QCRI scientists, including Dr. Raghvendra Mall, Dr. Halima Bensmail and Khalid Kunji, built a machine-learning algorithm that can identify the main regulators of separate brain tumors. Knowledge of the purpose of these … … The QCRI scientists, including Dr. Raghvendra Mall, Dr. Halima Bensmail and Khalid Kunji, built a machine-learning algorithm that can identify the main regulators of separate brain tumors. Knowledge of the purpose of …

… Ingmar Weber, Research Director for Social Computing, and Masoomali Fatehkia, Research Assistant at QCRI, explain how machine learning is helping to tackle poverty. Source:  www.electronicspecifier.com Related News … Ingmar Weber, Research Director for Social Computing, and Masoomali Fatehkia, Research Assistant at QCRI, explain how machine learning is helping to tackle poverty. Source:  www.electronicspecifier.com …

… fine grained propaganda detection task. More than 15 international teams over a period of 2 months worked on developing Machine Learning models capable of finding every instance of propaganda from a set of news articles. The participant’s system was … fine grained propaganda detection task. More than 15 international teams over a period of 2 months worked on developing Machine Learning models capable of finding every instance of propaganda from a set of news articles. The participant’s …

… Finding Pathways Beyond 2022 11 Jan 2020 Home Johanne Medina and Mohamed Amara constitute part of HBKU’s youngest learning cohorts, yet both have larger-than-life dreams. The students, who are enrolled in the College of Science and … platform, one that is unique and adaptable to the Qatari market. The application, which they dubbed QataGo, utilizes machine learning and smart web scraping technologies to curate and create individual profiles, guiding users through the … platform, one that is unique and adaptable to the Qatari market. The application, which they dubbed QataGo, utilizes machine learning and smart web scraping technologies to curate and create individual profiles, guiding users through the …

… informed a paper accepted at the Journal of Diabetes Research and Clinical Practice which concluded that XGBoost, a machine learning AI algorithm, achieved high predictive performance for normal and hyperglycemic excursions. The same application … informed a paper accepted at the Journal of Diabetes Research and Clinical Practice which concluded that XGBoost, a machine learning AI algorithm, achieved high predictive performance for normal and hyperglycemic excursions. The same …

… a scientist at QBRI’s Diabetes Research Center, and Dr. Halima Bensmail, a principal scientist at QCRI. Using machine learning techniques, the researchers analyzed the associations between prediabetes and data of approximately 8,000 … a scientist at QBRI’s Diabetes Research Center, and Dr. Halima Bensmail, a principal scientist at QCRI. Using machine learning techniques, the researchers analyzed the associations between prediabetes and data of approximately …

… expectations of QNRF. Can you tell us about your research projects that led to you receiving the scholarship? I am using machine learning technologies and trying to apply them to the field of sports athletes’ performance and injury analysis, … expectations of QNRF. Can you tell us about your research projects that led to you receiving the scholarship? I am using machine learning technologies and trying to apply them to the field of sports athletes’ performance and injury analysis, …

… Topics to be covered include waterflooding, gas flooding, water alternating gas (WAG), the use of data analytics and machine learning for optimizing oil and gas field development and reservoir management, well injectivity, productivity and … Topics to be covered include waterflooding, gas flooding, water alternating gas (WAG), the use of data analytics and machine learning for optimizing oil and gas field development and reservoir management, well injectivity, productivity …

… drive efficiencies in managing traffic, sports events, infrastructure, and urban spaces using big data management, deep learning, artificial intelligence (AI), and machine learning. At HBKU’s interactive stand, faculty and researchers were present to engage and share their insights … events, infrastructure, and urban spaces using big data management, deep learning, artificial intelligence (AI), and machine learning. At HBKU’s interactive stand, faculty and researchers were present to engage and share their insights …

… developed an AI-enabled system for the identification and stratification of obesity-related risk factors. The proposed machine learning model achieved over 90% accuracy, thereby outperforming the existing state-of-the-art models. Our system was … developed an AI-enabled system for the identification and stratification of obesity-related risk factors. The proposed machine learning model achieved over 90% accuracy, thereby outperforming the existing state-of-the-art models. Our system …