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Autor:
Tommaso Vincenzo Bartolotta, Ramona Woitek, Alessia Angela Maria Orlando, Giorgio Ivan Russo, Leonardo Rundo, Mariangela Dimarco, Carmelo Militello, Ildebrando D’Angelo
Publikováno v:
Academic radiology 29 (2022): 830–840. doi:10.1016/j.acra.2021.08.024
info:cnr-pdr/source/autori:Militello, Carmelo; Rundo, Leonardo; Dimarco, Mariangela; Orlando, Alessia; Woitek, Ramona; D'Angelo, Ildebrando; Russo, Giorgio; Bartolotta, Tommaso Vincenzo/titolo:3D DCE-MRI Radiomic Analysis for Malignant Lesion Prediction in Breast Cancer Patients/doi:10.1016%2Fj.acra.2021.08.024/rivista:Academic radiology/anno:2022/pagina_da:830/pagina_a:840/intervallo_pagine:830–840/volume:29
info:cnr-pdr/source/autori:Militello, Carmelo; Rundo, Leonardo; Dimarco, Mariangela; Orlando, Alessia; Woitek, Ramona; D'Angelo, Ildebrando; Russo, Giorgio; Bartolotta, Tommaso Vincenzo/titolo:3D DCE-MRI Radiomic Analysis for Malignant Lesion Prediction in Breast Cancer Patients/doi:10.1016%2Fj.acra.2021.08.024/rivista:Academic radiology/anno:2022/pagina_da:830/pagina_a:840/intervallo_pagine:830–840/volume:29
Rationale and Objectives: To develop and validate a radiomic model, with radiomic features extracted from breast Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) from a 1.5T scanner, for predicting the malignancy of masses with enhancem
Autor:
Dionysis Athanasopoulos, Dewei Liu
Publikováno v:
Athanasopoulos, D & Liu, D 2021, ' AI Back-End as a Service for Learning Switching of Mobile Apps between the Fog and the Cloud ', IEEE Transactions on Services Computing . https://doi.org/10.1109/TSC.2021.3117927
Given that cloud servers are usually remotely located from the devices of mobile apps, the end-users of the apps can face delays. The Fog has been introduced to augment the apps with machines located at the network edge close to the end-users. Howeve
Publikováno v:
Saied, I, Arslan, T & Chandran, S 2021, ' Classification of Alzheimers Disease using RF Signals and Machine Learning ', IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology . https://doi.org/10.1109/JERM.2021.3096172
Alzheimers disease is one of the most fastest growing and costly diseases in the world today. It affects the livelihood of not just patients, but those who take care of them, including care givers, nurses, and close family members. Current progressio
Publikováno v:
COMPEL - The international journal for computation and mathematics in electrical and electronic engineering. 41:807-823
Purpose This study aims to realize a sensorless metal object detection (MOD) using machine learning, to prevent the wireless power transfer (WPT) system from the risks of electric discharge and fire accidents caused by foreign metal objects. Design/m
Autor:
Mohammad Mehdi Aslani, Stefan Seipel
Publikováno v:
Information Sciences. 577:579-598
Support vector machines (SVMs) are powerful classifiers that have high computational complexity in the training phase, which can limit their applicability to large datasets. An effective approach to address this limitation is to select a small subset
Design and analysis of quantum powered support vector machines for malignant breast cancer diagnosis
Publikováno v:
Journal of Intelligent Systems, Vol 30, Iss 1, Pp 998-1013 (2021)
The rapid pace of development over the last few decades in the domain of machine learning mirrors the advances made in the field of quantum computing. It is natural to ask whether the conventional machine learning algorithms could be optimized using
Publikováno v:
Artificial intelligence review 55 (2022): 254–289. doi:10.1007/s10462-021-10032-0
info:cnr-pdr/source/autori:Murari A; Gelfusa M.; Lungaroni M.; Gauio P.; Peluso E./titolo:A systemic approach to classification for knowledge discovery with applications to the identification of boundary equations in complex systems/doi:10.1007%2Fs10462-021-10032-0/rivista:Artificial intelligence review/anno:2022/pagina_da:254/pagina_a:289/intervallo_pagine:254–289/volume:55
info:cnr-pdr/source/autori:Murari A; Gelfusa M.; Lungaroni M.; Gauio P.; Peluso E./titolo:A systemic approach to classification for knowledge discovery with applications to the identification of boundary equations in complex systems/doi:10.1007%2Fs10462-021-10032-0/rivista:Artificial intelligence review/anno:2022/pagina_da:254/pagina_a:289/intervallo_pagine:254–289/volume:55
Classification, which means discrimination between examples belonging to different classes, is a fundamental aspect of most scientific and engineering activities. Machine Learning (ML) tools have proved to be very performing in this task, in the sens
Autor:
Xiaoyu Luo
Publikováno v:
Alexandria Engineering Journal, Vol 60, Iss 3, Pp 3401-3409 (2021)
Text classification (TC) is an approach used for the classification of any kind of documents for the target category or out. In this paper, we implemented the Support Vector Machines (SVM) model in classifying English text and documents. Here we did
Autor:
Elisa Baroja, Eva Pilar Pérez-Álvarez, N. L. da Costa, Teresa Garde-Cerdán, I. Sáenz de Urturi, Rommel M. Barbosa, J. M. Martínez-Vidaurre, Pilar Rubio-Bretón, S. Marín-San Román
Publikováno v:
Digital.CSIC. Repositorio Institucional del CSIC
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A study in order to differentiate Tempranillo and Tempranillo blanco grapes and wines from A.O.C. Rioja (Spain) has been carried out. The three most important groups of chemical compounds in grapes and wines were determined: nitrogen and phenolic com
Autor:
Simona Crea, Vito Papapicco, Emanuele Gruppioni, Rinaldo Sacchetti, Angelo Davalli, Baojun Chen, Nicola Vitiello, Marko Munih
Publikováno v:
IEEE Transactions on Medical Robotics and Bionics. 3:436-445
Current state-of-the-art locomotion mode classifiers for controlling robotic lower-limb prostheses rely on multiple sensors to achieve high accuracy, prediction performance, and robustness to both speed changes and subject-specific gait patterns. How