FERDINANDO CALABRIA¹, ANTONIO BAGNATO¹, GIULIANA GUADAGNINO², MARIA TOTEDA¹, ANTONIO LANZILLOTTA¹, STEFANIA CARDEI¹, ROSANNA TAVOLARO¹, MARIO LEPORACE^1,*

Oncology Research, Vol.31, No.2, pp. 117-124, 2023, DOI:10.32604/or.2023.027705 - 10 April 2023

Abstract We observed several patients presenting 2-[¹⁸F]FDG uptake in the reactive axillary lymph node at PET/CT imaging, ipsilateral to the site of the COVID-19 vaccine injection. Analog finding was documented at [¹⁸F]Choline PET/CT. The aim of our study was to describe this source of false positive cases. All patients examined by PET/CT were included in the study. Data concerning patient anamnesis, laterality, and time interval from recent COVID-19 vaccination were recorded. SUVmax was measured in all lymph nodes expressing tracer uptake after vaccination. Among 712 PET/CT scans with 2-[¹⁸F]FDG, 104 were submitted to vaccination; 89/104 patients (85%) presented… More >

V. A. Vijayakumar^*, J. Shanthini, S. Karthik, K. Srihari

Computer Systems Science and Engineering, Vol.45, No.1, pp. 659-669, 2023, DOI:10.32604/csse.2023.028400 - 16 August 2022

Abstract The autonomous driving aims at ensuring the vehicle to effectively sense the environment and use proper strategies to navigate the vehicle without the interventions of humans. Hence, there exist a prediction of the background scenes and that leads to discontinuity between the predicted and planned outputs. An optimal prediction engine is required that suitably reads the background objects and make optimal decisions. In this paper, the author(s) develop an autonomous model for vehicle driving using ensemble model for large Sport Utility Vehicles (SUVs) that uses three different modules involving (a) recognition model, (b) planning model… More >