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Sara Rajaram and Cassie S. Mitchell
The ability to translate Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) into different modalities and data types is essential to improve Deep Learning (DL) for predictive medicine. This work presents DACMVA, a novel framework ...
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Pedro Romero-Gomez, Thanasak Poomchaivej, Rajesh Razdan, Wayne Robinson, Rudolf Peyreder, Michael Raeder and Lee J. Baumgartner
Fish protection is a priority in regions with ongoing and planned development of hydropower production, like the Mekong River system. The evaluation of the effects of turbine passage on the survival of migratory fish is a primary task for informing hydro...
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Nermin Abdelhakim Othman, Manal A. Abdel-Fattah and Ahlam Talaat Ali
Because of technological advancements and their use in the medical area, many new methods and strategies have been developed to address complex real-life challenges. Breast cancer, a particular kind of tumor that arises in breast cells, is one of the mos...
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Dimitris Papathanasiou, Konstantinos Demertzis and Nikos Tziritas
With the rapid growth of cloud computing and the creation of large-scale systems such as IoT environments, the failure of machines/devices and, by extension, the systems that rely on them is a major risk to their performance, usability, and the security ...
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Xinghui Li, Yang Yu, Cheng Zheng, Yue Zhang, Chuandao Shi, Lei Zhang and Hui Qiao
Studies on the prognostic significance of preoperative radiotherapy (PERT) and postoperative radiotherapy (PORT) in patients with advanced gastric cancer (GC) remain elusive. The aim of the study was to evaluate the survival advantage of preoperative and...
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Jöran Rixen, Nico Blass, Simon Lyra and Steffen Leonhardt
Breast cancer is the leading cause of cancer-related death among women. Early prediction is crucial as it severely increases the survival rate. Although classical X-ray mammography is an established technique for screening, many eligible women do not con...
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Shunsuke Kitada, Hitoshi Iyatomi and Yoshifumi Seki
This work can be applied to support decisions to discontinue ad creatives, which is expected to reduce the load of ad operators. Currently, our framework is deployed in a production environment and provides predictions for our internal operators. Based o...
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Gianfranco Lombardo, Mattia Pellegrino, George Adosoglou, Stefano Cagnoni, Panos M. Pardalos and Agostino Poggi
Predicting corporate bankruptcy is one of the fundamental tasks in credit risk assessment. In particular, since the 2007/2008 financial crisis, it has become a priority for most financial institutions, practitioners, and academics. The recent advancement...
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Nguyen Hong Nguyen and Pham Van Khang
To date, it is not known whether animal breeding values in Asian seabass (Lates calcarifer) can be estimated using single nucleotide polymorphisms (SNPs) generated from new high-throughput genotyping by sequencing platforms. The principal aim of the pres...
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Ronel J. Cassim,Matthys J. Swanepoel
AbstractOrientation: The effective and timely bankruptcy prediction is crucial to the survival of companies. In order to attain a desired result an effective bankruptcy prediction tool needs to be applied within a South African context.Research purpose: ...
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