Leveraging Spatial and Semantic Feature Extraction for Skin Cancer Diagnosis with Capsule Networks and Graph Neural Networks

Autor: Santoso, K. P., Ginardi, R. V. H., Sastrowardoyo, R. A., Madany, F. A.

In the realm of skin lesion image classification, the intricate spatial and semantic features pose significant challenges for conventional Convolutional Neural Network (CNN)-based methodologies. These challenges are compounded by the imbalanced natur

Externí odkaz: http://arxiv.org/abs/2403.12009

Information Technology Governance Analysis to Reduce Information Security Risks Using Cobit 2019: A Case Study of Manufacturing Companies.

Autor: Nugroho, Aditia, Ginardi, Hari

Publikováno v: Jurnal Indonesia Sosial Teknologi; Aug2024, Vol. 5 Issue 8, p3721-3733, 13p

The Rate of Seller Correctness in Naming Batik Solo Pattern: Studied in Indonesia Online Marketplace

Autor: Berlian Rahmy Lidiawaty, Mohammad Isa Irawan, Raden Venantius Hari Ginardi

Publikováno v: Jurnal Sosial Humaniora, Vol Special Edition 2020, Iss 1, Pp 80-93 (2020)

Every pattern in batik Solo has different meaning that affects its use. There are patterns for cultural ceremony, including funerals. Therefore, the seller of batik Solo’s product have to be able to give the right title as the name of its product i

Externí odkaz: https://doaj.org/article/64c9b85b52014970a9c5a4586cfc8d80

Anomaly detection on flight route using similarity and grouping approach based-on automatic dependent surveillance-broadcast

Autor: Mohammad Yazdi Pusadan, Joko Lianto Buliali, Raden Venantius Hari Ginardi

Publikováno v: IJAIN (International Journal of Advances in Intelligent Informatics), Vol 5, Iss 3, Pp 285-296 (2019)

Flight anomaly detection is used to determine the abnormal state data on the flight route. This study focused on two groups: general aviation habits (C1)and anomalies (C2). Groups C1 and C2 are obtained through similarity test with references. The me

Externí odkaz: https://doaj.org/article/39bbdf0fca0f47e2aa325fe0240735f9

Implementation of the ERAS (Enhanced Recovery After Surgery) protocol for colorectal cancer surgery in the Piemonte Region with an Audit and Feedback approach: study protocol for a stepped wedge cluster randomised trial: a study of the EASY-NET project

Autor: Eva Pagano, Dario Ribero, Oscar Bertetto, Paolo Massucco, Giovannino Ciccone, Fabio Saccona, Mauro Santarelli, Monica Carrera, Marco Brunetti, Roberto Rimonda, Francesca Cravero, Eliana Giaminardi, Francesco Battafarano, Alfredo Mellano, Enrico Gibin, Paola Bellomo, Sarah Palmisano, Luca Pellegrino, Federica Rinaldi, Valentina Palazzo, Danilo Donati, Maurizio Meineri, Monica Rolfo, Ilaria Bachini, Felice Borghi, Federica Borromeo, Fabio Priora, Sergio Gentilli, Luca Portigliotti, Marco Palisi, Maurizio De Giuli, Aridai Resendiz, Silvia Marola, Roberto Polastri, Andrea Muratore, Nicoletta Sveva Pipitone, Mauro Garino, Elisabetta Castagna, Gabriele Pozzo, Andrea Caneparo, Adriana Ginardi, Reggina Lagana, Stefania Muzio, Luca Panier Suffat, Ivan Lettini, Alberto Kiss, Valentina Gentile, Roberto Saracco, Donatella Scaglione, Andrea Gattolin, Luigi Oragano, Luca Lorenzin, Carlo Palenzona, Carmine Gianfranco Di Somma, Marco Calgaro, Marco Naddeo, Piero Cumbo, Emma Marchigiano, Marco Amisano, Francesco Lemut, Tiziana Viora, Luciano Bonaccorsi, Silvio Testa, Clemente De Rosa, Matteo Gatti, Carlo Bima, Francesco Quaglino, Federico Festa, Luca Bonatti, Mario Morino, Marco Ettore Allaix, Paolo De Paolis, Ida Marina Raciti, Gitana Scozzari, Rosalba Galletti, Sergio Sandrucci, Anna De Magistris, Barbara Mitola, Alessio Rizzo, Pietro Caironi, Anna Orlando, Francesco Brunetti, Corinna Defilè, Vitor Hugo Martins, Lisa Giacometti, Matteo Papurello, Danila Turco

Publikováno v: BMJ Open, Vol 11, Iss 6 (2021)

Introduction The ERAS protocol (Enhanced Recovery After Surgery) is a multimodal pathway aimed to reduce surgical stress and to allow a rapid postoperative recovery. Application of the ERAS protocol to colorectal cancer surgery has been limited to a

Externí odkaz: https://doaj.org/article/bfa0e6a861bd4529ae46cbef012a3910