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Institution

University of Siena

EducationSiena, Italy
About: University of Siena is a education organization based out in Siena, Italy. It is known for research contribution in the topics: Population & Cancer. The organization has 12179 authors who have published 33334 publications receiving 1008287 citations. The organization is also known as: Università degli studi di Siena & Universita degli studi di Siena.


Papers
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Journal ArticleDOI
TL;DR: A review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB) on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data.

12,097 citations

Journal ArticleDOI
01 Nov 2009-Thyroid
TL;DR: Evidence-based recommendations are developed to inform clinical decision-making in the management of thyroid nodules and differentiated thyroid cancer and represent, in the authors' opinion, contemporary optimal care for patients with these disorders.
Abstract: Background: Thyroid nodules are a common clinical problem, and differentiated thyroid cancer is becoming increasingly prevalent. Since the American Thyroid Association's (ATA's) guidelines for the management of these disorders were revised in 2009, significant scientific advances have occurred in the field. The aim of these guidelines is to inform clinicians, patients, researchers, and health policy makers on published evidence relating to the diagnosis and management of thyroid nodules and differentiated thyroid cancer. Methods: The specific clinical questions addressed in these guidelines were based on prior versions of the guidelines, stakeholder input, and input of task force members. Task force panel members were educated on knowledge synthesis methods, including electronic database searching, review and selection of relevant citations, and critical appraisal of selected studies. Published English language articles on adults were eligible for inclusion. The American College of Physicians Guideline Gr...

10,501 citations

Journal ArticleDOI
B. P. Abbott1, Richard J. Abbott1, T. D. Abbott2, Matthew Abernathy1  +1008 moreInstitutions (96)
TL;DR: This is the first direct detection of gravitational waves and the first observation of a binary black hole merger, and these observations demonstrate the existence of binary stellar-mass black hole systems.
Abstract: On September 14, 2015 at 09:50:45 UTC the two detectors of the Laser Interferometer Gravitational-Wave Observatory simultaneously observed a transient gravitational-wave signal. The signal sweeps upwards in frequency from 35 to 250 Hz with a peak gravitational-wave strain of $1.0 \times 10^{-21}$. It matches the waveform predicted by general relativity for the inspiral and merger of a pair of black holes and the ringdown of the resulting single black hole. The signal was observed with a matched-filter signal-to-noise ratio of 24 and a false alarm rate estimated to be less than 1 event per 203 000 years, equivalent to a significance greater than 5.1 {\sigma}. The source lies at a luminosity distance of $410^{+160}_{-180}$ Mpc corresponding to a redshift $z = 0.09^{+0.03}_{-0.04}$. In the source frame, the initial black hole masses are $36^{+5}_{-4} M_\odot$ and $29^{+4}_{-4} M_\odot$, and the final black hole mass is $62^{+4}_{-4} M_\odot$, with $3.0^{+0.5}_{-0.5} M_\odot c^2$ radiated in gravitational waves. All uncertainties define 90% credible intervals.These observations demonstrate the existence of binary stellar-mass black hole systems. This is the first direct detection of gravitational waves and the first observation of a binary black hole merger.

9,596 citations

Journal ArticleDOI
04 Nov 2009-Thyroid
TL;DR: Evidence-based recommendations in response to the appointment as an independent task force by the American Thyroid Association to assist in the clinical management of patients with thyroid nodules and differentiated thyroid cancer represent, in the authors' opinion, contemporary optimal care for patients with these disorders.
Abstract: Background: Thyroid nodules are a common clinical problem, and differentiated thyroid cancer is becoming increasingly prevalent. Since the publication of the American Thyroid Association's guidelines for the management of these disorders was published in 2006, a large amount of new information has become available, prompting a revision of the guidelines. Methods: Relevant articles through December 2008 were reviewed by the task force and categorized by topic and level of evidence according to a modified schema used by the United States Preventative Services Task Force. Results: The revised guidelines for the management of thyroid nodules include recommendations regarding initial evaluation, clinical and ultrasound criteria for fine-needle aspiration biopsy, interpretation of fine-needle aspiration biopsy results, and management of benign thyroid nodules. Recommendations regarding the initial management of thyroid cancer include those relating to optimal surgical management, radioiodine remnant ablation, a...

7,525 citations

Journal ArticleDOI
TL;DR: A new neural network model, called graph neural network (GNN) model, that extends existing neural network methods for processing the data represented in graph domains, and implements a function tau(G,n) isin IRm that maps a graph G and one of its nodes n into an m-dimensional Euclidean space.
Abstract: Many underlying relationships among data in several areas of science and engineering, e.g., computer vision, molecular chemistry, molecular biology, pattern recognition, and data mining, can be represented in terms of graphs. In this paper, we propose a new neural network model, called graph neural network (GNN) model, that extends existing neural network methods for processing the data represented in graph domains. This GNN model, which can directly process most of the practically useful types of graphs, e.g., acyclic, cyclic, directed, and undirected, implements a function tau(G,n) isin IRm that maps a graph G and one of its nodes n into an m-dimensional Euclidean space. A supervised learning algorithm is derived to estimate the parameters of the proposed GNN model. The computational cost of the proposed algorithm is also considered. Some experimental results are shown to validate the proposed learning algorithm, and to demonstrate its generalization capabilities.

5,701 citations


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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202391
2022221
20211,870
20201,979
20191,639
20181,523