Results 41 to 50 of about 102,167 (290)
Predicting Diabetes Mellitus With Machine Learning Techniques
Frontiers in Genetics, 2018 Diabetes mellitus is a chronic disease characterized by hyperglycemia. It may cause many complications. According to the growing morbidity in recent years, in 2040, the world’s diabetic patients will reach 642 million, which means that one of the ten ...
Quan Zou +6 more
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Energies, 2021 This work proposes a data-driven methodology for identifying critical components in Complex Technical Infrastructures (CTIs), for which the functional logic and/or the system structure functions are not known due the CTI’s complexity and evolving nature.
Ahmed Shokry +4 more
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Feature name and associated ranking.
, 2020 Feature name and associated ranking.
Md. Raihan-Al-Masud (8415444) +1 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Osteosarcoma (OS) and Ewing sarcoma (EWS) are the most common primary bone cancers in children, but acute thrombosis is poorly characterized in this population. Our study evaluated the rates of venous thromboembolism (VTE) and associated risk factors in pediatric patients with bone sarcomas treated over a 10‐year period encompassing
Sarah Kappa +8 more
wiley +1 more source
A novel somatic cancer gene-based biomedical document feature ranking and clustering model
Informatics in Medicine Unlocked, 2019 Background: As the size of somatic genomes in biomedical repositories increases, it is essential to predict cancer related document sets using the machine learning models. Most of the traditional gene-based somatic cancer mining models are independent of
Thulasi Bikku, Radhika Paturi
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Mathematics, 2023 In this paper, we propose and compare new methodologies for ranking the importance of variables in productive processes via an adaptation of OneClass Support Vector Machines.
Raul Moragues +2 more
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Learning to Rank 3D Features [PDF]
, 2014 Representation of three dimensional objects using a set of oriented point pair features has been shown to be effective for object recognition and pose estimation. Combined with an efficient voting scheme on a generalized Hough space, existing approaches achieve good recognition accuracy and fast operation.
Oncel Tuzel +3 more
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Feature Transformation for Neural Ranking Models [PDF]
Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020 Although neural network models enjoy tremendous advantages in handling image and text data, tree-based models still remain competitive for learning-to-rank tasks with numerical data. A major strength of tree-based ranking models is the insensitivity to different feature scales, while neural ranking models may suffer from features with varying scales or
Honglei Zhuang +3 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background An internal tandem duplication in the gene encoding Fms‐like tyrosine kinase 3 (FLT3‐ITD) is associated with high relapse risk and poor prognosis in acute myeloid leukemia (AML) and plays a crucial role in treatment decisions. Measurable residual disease (MRD) analysis of FLT3‐ITD during and after treatment has shown prognostic ...
Sofie Johansson Alm +11 more
wiley +1 more source
Pairwise meta-rules for better meta-learning-based algorithm ranking
, 2013 In this paper, we present a novel meta-feature generation method in the context of meta-learning, which is based on rules that compare the performance of individual base learners in a one-against-one manner.
Pfahringer, Bernhard, Sun, Quan
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