A5091031858- Radiation Therapy and Dosimetry
- Radiation Detection and Scintillator Technologies
- Advanced Radiotherapy Techniques
- Radiation Effects in Electronics
- Economic and Technological Innovation
- Particle Detector Development and Performance
- Boron Compounds in Chemistry
- Innovation and Knowledge Management
- Brain Tumor Detection and Classification
- Parallel Computing and Optimization Techniques
- Firm Innovation and Growth
- Innovation and Socioeconomic Development
- Advanced Neural Network Applications
- Nuclear Physics and Applications
- Computational Physics and Python Applications
- Generative Adversarial Networks and Image Synthesis
- Data Visualization and Analytics
- Lymphatic System and Diseases
- Advanced Graph Neural Networks
Istituto Nazionale di Fisica Nucleare, Sezione di Roma I
2023-2025
Sapienza University of Rome
2021-2025
Lipoedema is a subcutaneous adipose tissue disease characterized by the increase in amount and structure of fat mass (FM) specific areas, causing pain discomfort. 95% patients fail to lose weight lipoedema areas. The study was conducted evaluate body composition general health status modification group (LIPPY) control (CTRL) after four weeks modified Mediterranean diet therapy (mMeD). A total 29 subjects were included data analysis, divided two groups: 14 LIPPY 15 CTRL. After mMeD, both...
Geant4, a Monte Carlo Simulation Toolkit extensively used in bio-medical physics, is continuous evolution to include newest research findings improve its accuracy and respond the evolving needs of very diverse user community. In 2014, G4-Med benchmarking system was born from effort Geant4 Medical Benchmarking Group, benchmark monitor for medical physics applications. The first described our Physics Special Report published 2021. Results tests were reported 10.5. this work, we describe...
The treatment of deep-seated tumours with electrons very high energies (VHEE, 70–150 MeV) has already been explored in the past, suggesting that a dosimetric coverage comparable state-of-the-art proton (PT) or photon radiotherapy (RT) could be achieved large ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m1"><mml:mo>></mml:mo></mml:math> 10) number fields and electron energy. technical economical challenges posed by deployment such beams centres, together expected small...
Mergers and Acquisitions represent important forms of business deals, both because the volumes involved in transactions role innovation activity companies. Nevertheless, Economic Complexity methods have not been applied to study this field. By considering patent about one thousand companies, we develop a method predict future acquisitions by assuming that companies deal more frequently with technologically related ones. We address problem predicting pair for finding target company given an...
In this article we examine recent developments in the research area concerning creation of end-to-end models for complete optimization measuring instruments. The consider rely on differentiable programming methods and specification a software pipeline including all factors impacting performance -- from data-generating processes to their reconstruction extraction inference parameters interest instrument along with careful utility function well aligned end goals experiment. Building previous...
Introduction External beam radiotherapy (RT) is one of the most common treatments against cancer, with photon-based RT and particle therapy being commonly employed modalities. Very high energy electrons (VHEE) have emerged as promising candidates for novel treatments, particularly in exploiting FLASH effect, offering potential advantages over traditional Methods This paper introduces a Deep Learning model based on graph convolutional networks to determine dose distributions therapeutic VHEE...
Graphs are versatile structures for the representation of many real-world data. Deep Learning on graphs is currently able to solve a wide range problems with excellent results. However, both generation and handling large still remain open challenges. This work aims introduce techniques generating test approach complex problem such as calculation dose distribution in oncological radiotherapy applications. To this end, we introduced pooling technique (ReNN-Pool) capable sampling nodes that...
We present a Deep Learning generative model specialized to work with graphs regular geometry. It is build on Variational Autoencoder framework and employs Graph convolutional layers in both encoding decoding phases. also introduce pooling technique (ReNN-Pool), used the encoder, that allows downsample graph nodes spatially uniform highly interpretable way. In decoder, symmetrical un-pooling retrieve original dimensionality of graphs. Performance are tested standard Sprite benchmark dataset,...
Mergers and Acquisitions represent important forms of business deals, both because the volumes involved in transactions role innovation activity companies. Nevertheless, Economic Complexity methods have not been applied to study this field. By considering patent about one thousand companies, we develop a method predict future acquisitions by assuming that companies deal more frequently with technologically related ones. We address problem predicting pair for finding target company given an...