CRIS Current Research Information System

MOTTOLA, MARGHERITA
 Distribuzione geografica
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Continente #
EU - Europa 2.362
AS - Asia 2.143
NA - Nord America 1.819
AF - Africa 100
SA - Sud America 90
OC - Oceania 6
Totale 6.520
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Nazione #
US - Stati Uniti d'America 1.794
GB - Regno Unito 890
CN - Cina 627
SG - Singapore 581
IT - Italia 475
DE - Germania 312
IN - India 249
VN - Vietnam 209
SE - Svezia 169
KR - Corea 120
HK - Hong Kong 117
IR - Iran 91
FI - Finlandia 86
FR - Francia 85
RU - Federazione Russa 83
NL - Olanda 66
BR - Brasile 61
IE - Irlanda 55
TR - Turchia 36
ZA - Sudafrica 29
TG - Togo 27
AT - Austria 26
JP - Giappone 25
JO - Giordania 22
ID - Indonesia 17
CH - Svizzera 15
SC - Seychelles 15
CA - Canada 14
AR - Argentina 13
PL - Polonia 13
UA - Ucraina 13
HR - Croazia 12
MY - Malesia 12
CI - Costa d'Avorio 11
EE - Estonia 11
BG - Bulgaria 10
ES - Italia 10
PK - Pakistan 9
PH - Filippine 8
RO - Romania 7
AU - Australia 6
BD - Bangladesh 6
IL - Israele 6
AL - Albania 5
CL - Cile 5
MX - Messico 5
GR - Grecia 4
NG - Nigeria 4
BE - Belgio 3
CR - Costa Rica 3
EC - Ecuador 3
EG - Egitto 3
GH - Ghana 3
PT - Portogallo 3
LB - Libano 2
MA - Marocco 2
PA - Panama 2
PE - Perù 2
RS - Serbia 2
TH - Thailandia 2
UY - Uruguay 2
BA - Bosnia-Erzegovina 1
BF - Burkina Faso 1
BO - Bolivia 1
BY - Bielorussia 1
CG - Congo 1
CO - Colombia 1
CZ - Repubblica Ceca 1
DK - Danimarca 1
DO - Repubblica Dominicana 1
DZ - Algeria 1
GE - Georgia 1
GY - Guiana 1
HU - Ungheria 1
IQ - Iraq 1
KZ - Kazakistan 1
LT - Lituania 1
MU - Mauritius 1
NA - Namibia 1
PY - Paraguay 1
SK - Slovacchia (Repubblica Slovacca) 1
UG - Uganda 1
UZ - Uzbekistan 1
Totale 6.520
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Città #
Southend 791
Singapore 413
Chandler 261
Ashburn 226
Hefei 200
Hyderabad 153
Dallas 136
Bologna 124
Hong Kong 103
Seoul 97
Munich 95
Santa Clara 77
Helsinki 67
Beijing 66
Wilmington 61
Fairfield 60
Princeton 56
Frankfurt am Main 55
Ho Chi Minh City 55
Houston 54
Dublin 53
Boardman 51
Los Angeles 45
Manchester 44
Hanoi 37
Dong Ket 34
Ann Arbor 33
Istanbul 32
Redmond 31
Milan 28
Cambridge 27
Lomé 27
Rome 23
Amman 22
Medford 22
Vienna 22
Seattle 21
Berlin 19
Modena 18
New York 18
Redondo Beach 17
Tokyo 17
Westminster 17
Woodbridge 17
Bengaluru 16
Kuban 16
Des Moines 14
The Dalles 14
Changsha 13
Turin 13
Buffalo 12
San Jose 12
Tongling 12
Abidjan 11
Guangzhou 11
London 10
Nanjing 10
Nuremberg 10
Olalla 10
Sofia 10
Basingstoke 9
Chennai 9
Jinan 9
San Diego 9
São Paulo 9
Jakarta 8
Miami 8
Reggio Emilia 8
Shenzhen 8
The Bronx 8
Council Bluffs 7
Fairport 7
Lappeenranta 7
Pietermaritzburg 7
Pocheon-si 7
Turku 7
Xi'an 7
Amsterdam 6
Augusta 6
Chicago 6
Falkenstein 6
Hebei 6
Novara 6
Peshawar 6
Redwood City 6
Seri Kembangan 6
Shenyang 6
St Louis 6
Washington 6
Bern 5
Bethesda 5
Brooklyn 5
Decatur 5
Delhi 5
Falls Church 5
Grafing 5
Haiphong 5
Hanover 5
Harringay 5
Montreal 5
Totale 4.280
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Nome #
Radiomic Features from Post-Operative 18F-FDG PET/CT and CT Imaging Associated with Locally Recurrent Rectal Cancer: Preliminary Findings 313
Locally advanced rectal cancer: T2w-MRI-based radiomics may detect responder patients undergoing neoadjuvant chemoradiotherapy 269
Human, All Too Human? An All-Around Appraisal of the “Artificial Intelligence Revolution” in Medical Imaging 256
mpMRI detection of suspected prostate cancer with a negative biopsy: can radiomic features help radiologists? 246
Radiomic features disclose the presence of microvascular invasion in hepatocellular carcinoma 238
Comparison of 68Ga-PSMA SUVmax and tumour heterogeneity in DW-MRI 218
Radiomics in DW-MRI detects non-clinically significant prostate cancer and reduces overtreatment 218
Prostate cancer heterogeneity in high b-value DWI correlates with [68Ga]-PSMA PET/CT: preliminary results 214
An Apparent Diffusion Coefficient-based machine learning model can improve Prostate Cancer detection in the grey area of the PI-RADS 3 category: a single-centre experience 208
Risk stratification of patients with prostate cancer: promising results with high b-value DWI radiomic features 207
Diffusion weighted imaging in prostate cancer: a descriptor of tumour habitat differentiates high-risk and low-risk lesions 202
Heterogeneity of skewness in T2w-MR images of locally advanced rectal cancer relates with response to neoadjuvant chemoradiotherapy 202
Reproducibility of Computed Tomography perfusion parameters in hepatic multicentre study in patients with colorectal cancer 192
CT perfusion of liver in patients with colorectal cancer allows discriminating patients who will develop liver metastases 189
Colormaps of CT perfusion parameters computed using different methods visually match 185
A patient-driven approach to improve reproducibility of blood flow values in CT perfusion of liver 176
The Heterogeneity of Skewness in T2W-Based Radiomics Predicts the Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer 172
Automatically extracted machine learning features from preoperative CT to early predict microvascular invasion in HCC: the role of the Zone of Transition (ZOT) 171
Extracting equilibrium Blood Flow (eBF) values of CTp liver perfusion from tissue peak: a new promising perfusion parameter 165
Blood flow assessment of liver in patients with colorectal cancer: results agreement in a Computed Tomography perfusion multicentre study 161
Prostate cancer staging based on high b-value diffusion weighted magnetic resonance imaging 161
L'Intelligenza Artificiale nella diagnosi precoce nell'invasione microvascolare nell'epatocarcinoma in stadio iniziale 155
Computer-based detection of colorectal serrated lesions: Digital flatness, a novel metric designed for whole-slide images 149
Predicting clinical evolution of prostate cancer in active surveillance: early suggestions from DW-MRI 148
CT perfusion maps of liver computed with different methods match 144
Beyond multiparametric MRI and towards radiomics to detect prostate cancer: A machine learning model to predict clinically significant lesions 141
To assess the role of radiomic features from high b-value DWI sequences in the early detection of clinically significant prostate cancer (PCa) 139
A radiomic signature for detecting prostate cancer with multi-parametric MRI 134
Beyond Multiparametric MRI and towards Radiomics to Detect Prostate Cancer: A Machine Learning Model to Predict Clinically Significant Lesions 132
LE PROPRIETÀ NASCOSTE NELL’IMMAGINE RM PER RILEVARE AUTOMATICAMENTE LA ZONA DI TRANSIZIONE TRA CARCINOMA RETTALE LOCALMENTE AVANZATO E TESSUTO SANO, E PREDIRE LA RISPOSTA ALLA TERAPIA NEO-ADIUVANTE 128
Errors of a controlled Time-Concentration Curve fitting in CT perfusion uniformly affect perfusion values computed with two different methods 128
Automatically Extracted Machine Learning Features from Preoperative CT to Early Predict Microvascular Invasion in HCC: The Role of the Zone of Transition (ZOT) 127
The Primacy of High b-Value 3T-DWI Radiomics in the Prediction of Clinically Significant Prostate Cancer 126
Beyond multiparametric MRI and towards radiomics to detect prostate cancer: A machine learning model to predict clinically significant lesions 124
Skewness of HPI as a suggestive biomarker to predict development of liver metastases in patients with colorectal cancer 124
null 111
Letter to the Editor on “Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review” 102
Reproducibility of CT-based radiomic features against image resampling and perturbations for tumour and healthy kidney in renal cancer patients 85
Analysis of the effects of fitting errors of DCE-CT signals on perfusion parameters 72
The effectiveness of an adaptive method to analyse the transition between tumour and peritumour for answering two clinical questions in cancer imaging 60
Totale 6.692
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Categoria #
all - tutte 18.281
article - articoli 0
book - libri 0
conference - conferenze 0
curatela - curatele 0
other - altro 0
patent - brevetti 0
selected - selezionate 0
volume - volumi 0
Totale 18.281
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Totale Lug Ago Sett Ott Nov Dic Gen Feb Mar Apr Mag Giu
2020/2021638 0 0 0 0 0 0 51 77 147 65 113 185
2021/2022823 48 63 41 40 106 42 43 63 84 24 166 103
2022/2023976 98 168 61 101 68 122 16 55 135 34 62 56
2023/2024728 30 59 39 53 47 252 36 71 34 41 35 31
2024/20251.368 63 116 86 96 159 99 200 62 49 124 124 190
2025/20261.604 265 363 339 177 270 150 40 0 0 0 0 0
Totale 6.692