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, 1998 This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The objective of this project was to develop and implement data mining technology suited to the analysis of large collections of unstructured data.
Parker, Julian, Sloan, Terence, Yau, Hon
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Mining Views: Database Views for Data Mining [PDF]
2008 IEEE 24th International Conference on Data Engineering, 2008 We present a system towards the integration of data mining into relational databases. To this end, a relational database model is proposed, based on the so called virtual mining views. We show that several types of patterns and models over the data, such as itemsets, association rules and decision trees, can be represented and queried using a unifying ...
Hendrik Blockeel +4 more
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Frontiers in Oncology, 2022 As one of the most common cancers of the digestive system, colon cancer is a predominant cause of cancer-related deaths worldwide. To investigate prognostic genes in the tumor microenvironment of colon cancer, we collected 461 colon adenocarcinoma (COAD)
Jinyang Liu +8 more
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Journal of Cloud Computing: Advances, Systems and Applications, 2022 Cloud computing has emerged as a promising paradigm for meeting the growing resource demands of Internet of Things (IoT) devices. Meanwhile, with the popularity of mobile aerial base stations, Unmanned Aerial Vehicle (UAV) assisted cloud computing is ...
Yu Zhou +4 more
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Applied Sciences, 2021 In many application domains such as medicine, information retrieval, cybersecurity, social media, etc., datasets used for inducing classification models often have an unequal distribution of the instances of each class.
Mohamed S. Kraiem +2 more
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Joint DNN partitioning and task offloading in mobile edge computing via deep reinforcement learning
Journal of Cloud Computing: Advances, Systems and Applications, 2023 As Artificial Intelligence (AI) becomes increasingly prevalent, Deep Neural Networks (DNNs) have become a crucial tool for developing and advancing AI applications.
Jianbing Zhang +3 more
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Scientific Programming, 2008 Biological data mining purports to extract useful knowledge from massive datasets gathered in biology, and in other related life sciences areas such as medicine and neuroscience. In the recent past, we have witnessed major transformations of these applied sciences into data-driven endeavors.
Zaki, Mohammed J. +2 more
openaire +1 more source
Data mining in clinical big data: the frequently used databases, steps, and methodological models
Military Medical Research, 2021 Many high quality studies have emerged from public databases, such as Surveillance, Epidemiology, and End Results (SEER), National Health and Nutrition Examination Survey (NHANES), The Cancer Genome Atlas (TCGA), and Medical Information Mart for ...
Wen-Tao Wu +6 more
semanticscholar +1 more source
CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories
IEEE Transactions on Knowledge and Data Engineering, 2021 CRISP-DM(CRoss-Industry Standard Process for Data Mining) has its origins in the second half of the nineties and is thus about two decades old. According to many surveys and user polls it is still the de facto standard for developing data mining and ...
Fernando Martínez-Plumed +7 more
semanticscholar +1 more source
Spearheading future omics analyses using dyngen, a multi-modal simulator of single cells
Nature Communications, 2021 To benchmark single cell bioinformatics tools, data simulators can provide a robust ground truth. Here the authors present dyngen, a multi-modal simulator, and apply it to aligning cell developmental trajectories, cell-specific regulatory network ...
Robrecht Cannoodt +3 more
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