CRIS Current Research Information System

MOTTOLA, MARGHERITA
 Distribuzione geografica
Salva come PNG Salva come JPEG
Continente #
AS - Asia 2.889
EU - Europa 2.490
NA - Nord America 2.154
SA - Sud America 134
AF - Africa 121
OC - Oceania 7
Continente sconosciuto - Info sul continente non disponibili 1
Totale 7.796
Salva come PNG Salva come JPEG
Nazione #
US - Stati Uniti d'America 2.119
GB - Regno Unito 909
CN - Cina 681
SG - Singapore 680
VN - Vietnam 553
IT - Italia 490
DE - Germania 326
IN - India 273
HK - Hong Kong 199
SE - Svezia 169
FR - Francia 129
KR - Corea 128
FI - Finlandia 100
IR - Iran 91
BR - Brasile 89
RU - Federazione Russa 83
NL - Olanda 69
JP - Giappone 62
IE - Irlanda 56
TR - Turchia 39
ZA - Sudafrica 34
PH - Filippine 30
AT - Austria 27
TG - Togo 27
JO - Giordania 23
ID - Indonesia 19
AR - Argentina 18
BD - Bangladesh 18
CA - Canada 18
CH - Svizzera 16
PK - Pakistan 16
SC - Seychelles 16
MY - Malesia 15
TH - Thailandia 15
UA - Ucraina 15
ES - Italia 14
PL - Polonia 14
CI - Costa d'Avorio 12
EE - Estonia 12
HR - Croazia 12
BG - Bulgaria 10
MX - Messico 10
IQ - Iraq 9
TW - Taiwan 8
AU - Australia 7
CL - Cile 7
RO - Romania 7
UZ - Uzbekistan 7
CO - Colombia 6
EC - Ecuador 6
EG - Egitto 6
IL - Israele 6
AL - Albania 5
GR - Grecia 5
PT - Portogallo 5
BE - Belgio 4
GH - Ghana 4
MA - Marocco 4
NG - Nigeria 4
SA - Arabia Saudita 4
CR - Costa Rica 3
DZ - Algeria 3
NP - Nepal 3
AE - Emirati Arabi Uniti 2
BY - Bielorussia 2
CG - Congo 2
HU - Ungheria 2
LB - Libano 2
PA - Panama 2
PE - Perù 2
RS - Serbia 2
SK - Slovacchia (Repubblica Slovacca) 2
TN - Tunisia 2
UY - Uruguay 2
AO - Angola 1
BA - Bosnia-Erzegovina 1
BF - Burkina Faso 1
BH - Bahrain 1
BO - Bolivia 1
BT - Bhutan 1
CD - Congo 1
CV - Capo Verde 1
CY - Cipro 1
CZ - Repubblica Ceca 1
DK - Danimarca 1
DO - Repubblica Dominicana 1
GE - Georgia 1
GY - Guiana 1
JM - Giamaica 1
KZ - Kazakistan 1
LT - Lituania 1
ME - Montenegro 1
MU - Mauritius 1
NA - Namibia 1
OM - Oman 1
PY - Paraguay 1
UG - Uganda 1
VE - Venezuela 1
XK - ???statistics.table.value.countryCode.XK??? 1
Totale 7.796
Salva come PNG Salva come JPEG
Città #
Southend 791
Singapore 503
Chandler 261
Ashburn 247
Hefei 201
Hong Kong 170
Hyderabad 157
San Jose 147
Dallas 137
Ho Chi Minh City 135
Hanoi 128
Bologna 124
Seoul 98
Munich 95
Santa Clara 82
Helsinki 73
Los Angeles 73
Beijing 69
Frankfurt am Main 65
Wilmington 61
Fairfield 60
Princeton 56
Houston 55
Boardman 53
Dublin 53
Council Bluffs 49
Manchester 48
Tokyo 48
Dong Ket 34
Lauterbourg 34
Ann Arbor 33
Istanbul 33
New York 32
Redmond 31
Milan 30
Cambridge 27
Lomé 27
The Dalles 25
Rome 24
Amman 23
Medford 22
Vienna 22
Seattle 21
Modena 20
Berlin 19
Haiphong 18
Redondo Beach 17
Westminster 17
Woodbridge 17
Bengaluru 16
Da Nang 16
Kuban 16
Guangzhou 15
Des Moines 14
London 14
São Paulo 14
Changsha 13
Orem 13
Turin 13
Abidjan 12
Basingstoke 12
Buffalo 12
Chennai 12
Nuremberg 12
Tongling 12
Nanjing 10
Olalla 10
Sofia 10
Amsterdam 9
Jinan 9
San Diego 9
Shenzhen 9
Jakarta 8
Miami 8
Montreal 8
Reggio Emilia 8
The Bronx 8
Xi'an 8
Augusta 7
Chicago 7
Fairport 7
Johannesburg 7
Lappeenranta 7
Pietermaritzburg 7
Pocheon-si 7
Shanghai 7
Tashkent 7
Turku 7
Delhi 6
Falkenstein 6
Hebei 6
Novara 6
Paris 6
Peshawar 6
Redwood City 6
Seodaemun-gu 6
Seri Kembangan 6
Shenyang 6
St Louis 6
Washington 6
Totale 5.037
Salva come PNG Salva come JPEG
Nome #
Radiomic Features from Post-Operative 18F-FDG PET/CT and CT Imaging Associated with Locally Recurrent Rectal Cancer: Preliminary Findings 346
Locally advanced rectal cancer: T2w-MRI-based radiomics may detect responder patients undergoing neoadjuvant chemoradiotherapy 304
Human, All Too Human? An All-Around Appraisal of the “Artificial Intelligence Revolution” in Medical Imaging 298
mpMRI detection of suspected prostate cancer with a negative biopsy: can radiomic features help radiologists? 275
Radiomic features disclose the presence of microvascular invasion in hepatocellular carcinoma 271
Comparison of 68Ga-PSMA SUVmax and tumour heterogeneity in DW-MRI 255
Radiomics in DW-MRI detects non-clinically significant prostate cancer and reduces overtreatment 254
Heterogeneity of skewness in T2w-MR images of locally advanced rectal cancer relates with response to neoadjuvant chemoradiotherapy 251
Prostate cancer heterogeneity in high b-value DWI correlates with [68Ga]-PSMA PET/CT: preliminary results 243
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 242
The Heterogeneity of Skewness in T2W-Based Radiomics Predicts the Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer 242
Risk stratification of patients with prostate cancer: promising results with high b-value DWI radiomic features 236
Diffusion weighted imaging in prostate cancer: a descriptor of tumour habitat differentiates high-risk and low-risk lesions 230
Reproducibility of Computed Tomography perfusion parameters in hepatic multicentre study in patients with colorectal cancer 228
Prostate cancer staging based on high b-value diffusion weighted magnetic resonance imaging 226
Colormaps of CT perfusion parameters computed using different methods visually match 215
Automatically extracted machine learning features from preoperative CT to early predict microvascular invasion in HCC: the role of the Zone of Transition (ZOT) 208
A patient-driven approach to improve reproducibility of blood flow values in CT perfusion of liver 205
CT perfusion of liver in patients with colorectal cancer allows discriminating patients who will develop liver metastases 205
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 200
Computer-based detection of colorectal serrated lesions: Digital flatness, a novel metric designed for whole-slide images 193
Extracting equilibrium Blood Flow (eBF) values of CTp liver perfusion from tissue peak: a new promising perfusion parameter 192
Beyond multiparametric MRI and towards radiomics to detect prostate cancer: A machine learning model to predict clinically significant lesions 190
Blood flow assessment of liver in patients with colorectal cancer: results agreement in a Computed Tomography perfusion multicentre study 187
L'Intelligenza Artificiale nella diagnosi precoce nell'invasione microvascolare nell'epatocarcinoma in stadio iniziale 177
To assess the role of radiomic features from high b-value DWI sequences in the early detection of clinically significant prostate cancer (PCa) 175
Predicting clinical evolution of prostate cancer in active surveillance: early suggestions from DW-MRI 173
Beyond Multiparametric MRI and towards Radiomics to Detect Prostate Cancer: A Machine Learning Model to Predict Clinically Significant Lesions 166
Automatically Extracted Machine Learning Features from Preoperative CT to Early Predict Microvascular Invasion in HCC: The Role of the Zone of Transition (ZOT) 161
CT perfusion maps of liver computed with different methods match 161
A radiomic signature for detecting prostate cancer with multi-parametric MRI 158
The Primacy of High b-Value 3T-DWI Radiomics in the Prediction of Clinically Significant Prostate Cancer 149
Beyond multiparametric MRI and towards radiomics to detect prostate cancer: A machine learning model to predict clinically significant lesions 148
Errors of a controlled Time-Concentration Curve fitting in CT perfusion uniformly affect perfusion values computed with two different methods 147
Skewness of HPI as a suggestive biomarker to predict development of liver metastases in patients with colorectal cancer 141
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” 116
null 111
Reproducibility of CT-based radiomic features against image resampling and perturbations for tumour and healthy kidney in renal cancer patients 103
The effectiveness of an adaptive method to analyse the transition between tumour and peritumour for answering two clinical questions in cancer imaging 102
Analysis of the effects of fitting errors of DCE-CT signals on perfusion parameters 92
Totale 7.976
Salva come PNG Salva come JPEG
Categoria #
all - tutte 19.932
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 19.932
Salva come PNG Salva come JPEG


Totale Lug Ago Sett Ott Nov Dic Gen Feb Mar Apr Mag Giu
2020/2021363 0 0 0 0 0 0 0 0 0 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
2025/20262.888 265 363 339 177 270 150 467 89 530 238 0 0
Totale 7.976