G
Giuseppe De Pietro
Researcher at Indian Council of Agricultural Research
Publications - 263
Citations - 3638
Giuseppe De Pietro is an academic researcher from Indian Council of Agricultural Research. The author has contributed to research in topics: Decision support system & Computer science. The author has an hindex of 28, co-authored 241 publications receiving 2441 citations. Previous affiliations of Giuseppe De Pietro include National Research Council & Institute for High Performance Computing and Networking, CNR.
Papers
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Journal ArticleDOI
Voice Disorder Identification by Using Machine Learning Techniques
TL;DR: The key contribution of this paper is to investigate and compare the performance of several machine learning techniques useful for voice pathology detection and show that the best accuracy in voice diseases detection is achieved by the support vector machine algorithm or the decision tree one, depending on the features evaluated by using opportune feature selection methods.
Journal ArticleDOI
Virtual reality and music therapy as distraction interventions to alleviate anxiety and improve mood states in breast cancer patients during chemotherapy
Andrea Chirico,Andrea Chirico,Patrizia Maiorano,Paola Indovina,Paola Indovina,Carla Milanese,Carla Milanese,Giovan Giacomo Giordano,Fabio Alivernini,Giovanni Iodice,Luigi Gallo,Giuseppe De Pietro,Fabio Lucidi,Gerardo Botti,Michelino De Laurentiis,Antonio Giordano,Antonio Giordano +16 more
TL;DR: The data suggest that both VR and MT are useful interventions for alleviating anxiety and for improving mood states in breast cancer patients during chemotherapy, and VR seems more effective than MT in relieving anxiety, depression, and fatigue.
Proceedings ArticleDOI
3D interaction with volumetric medical data: experiencing the Wiimote
TL;DR: New flavors of existing 3D interaction techniques specifically designed for interacting with volumetric medical data in a semi-immersive virtual environment by using the Nintendo Wiimote controller as 3D user interface are presented.
Journal ArticleDOI
A Deep Learning Approach for Breast Invasive Ductal Carcinoma Detection and Lymphoma Multi-Classification in Histological Images
TL;DR: This paper explores deep learning methods for the automatic analysis of Hematoxylin and Eosin stained histological images of breast cancer and lymphoma and proposes a deep learning approach for two different use cases: the detection of invasive ductal carcinoma in breast histology images and the classification of lymphoma sub-types.
BookDOI
Intelligent Interactive Multimedia Systems and Services
TL;DR: Involving several thousand researchers, managers and engineers drawn from universities and companies world-wide, KES is in an excellent position to generate synergy in the area of arti- cial intelligence applied to real-world Smart systems and the underlying related theory.