MR Fingerprinting (MRF) is a relatively new imaging framework for MR acquisition, reconstruction, and analysis, which can provide rapid, efficient and simultaneous quantification of
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Who will be rich and poor in future? – Michio Kaku
Michio Kaku explains the main reason that will be a key factor in determining which countries will be poor and which will be rich
One Hundred Year Study on Artificial Intelligence
The One Hundred Year Study on Artificial Intelligence, launched in the fall of 2014, is a long-term investigation of the field of Artificial Intelligence
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Deep learning in business analytics and operations research: Models, applications and managerial implications What was once described by Davenport & Harris (2007) as “firms
Lung Nodule Detection from Feature Engineering to Deep Learning in Thoracic CT Images | Article
Cancer is a disease that has several manifestations and it is primarily associated with abnormal cell groups. These cancer cells continue to divide and
A Deep Learning Framework for Predicting Response to Therapy in Cancer
Sakellaropoulos et al. designed a machine learning workflow to predict drug response and survival of cancer patients. All pipelines are trained on a large panel
The Effects of Artificial Intelligence and Robotic Systems on Librarianship
With Industry 4.0, smart robots will be involved in all areas of our lives, and systems using technology control instead of work force will
Artificial Intelligence Seeks An Ethical Conscience
Leading Artificial-Intelligence Researchers gathered this week for the prestigious Neural Information Processing Systems conference have a new topic on their agenda. Alongside the usual cutting-edge
Deep learning predictions of galaxy merger stage and the importance of observational realism
Theoretical predictions and observations alike show that mergers transform galaxies. Stellar bridges and tails observed in interacting galaxy pairs are the relics of the
A novel deep learning neural network approach for predicting flash flood susceptibility
A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high-frequency tropical storm area This research proposes