IRIS
Mento, Federico
 Distribuzione geografica
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Continente #
NA - Nord America 5.099
AS - Asia 1.855
EU - Europa 1.657
SA - Sud America 321
Continente sconosciuto - Info sul continente non disponibili 229
AF - Africa 41
OC - Oceania 4
Totale 9.206
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Nazione #
US - Stati Uniti d'America 4.935
SG - Singapore 794
IT - Italia 786
CN - Cina 344
BR - Brasile 248
VN - Vietnam 242
RU - Federazione Russa 197
KR - Corea 107
GB - Regno Unito 97
CA - Canada 90
BD - Bangladesh 87
FR - Francia 87
SE - Svezia 79
DE - Germania 69
IN - India 69
FI - Finlandia 64
LV - Lettonia 64
NL - Olanda 62
HK - Hong Kong 59
IE - Irlanda 43
MX - Messico 25
BG - Bulgaria 24
AR - Argentina 22
TR - Turchia 19
ID - Indonesia 16
JP - Giappone 16
AT - Austria 15
IQ - Iraq 15
PL - Polonia 15
ES - Italia 14
TW - Taiwan 14
CL - Cile 13
EC - Ecuador 13
AE - Emirati Arabi Uniti 10
PK - Pakistan 9
SA - Arabia Saudita 9
ZA - Sudafrica 9
EG - Egitto 8
JM - Giamaica 8
UA - Ucraina 8
CR - Costa Rica 7
GT - Guatemala 7
CO - Colombia 6
DZ - Algeria 6
HN - Honduras 6
JO - Giordania 6
KE - Kenya 6
PE - Perù 6
PH - Filippine 6
CH - Svizzera 5
PT - Portogallo 5
SV - El Salvador 5
UY - Uruguay 5
BE - Belgio 4
CW - ???statistics.table.value.countryCode.CW??? 4
DK - Danimarca 4
IL - Israele 4
NP - Nepal 4
OM - Oman 4
AU - Australia 3
CZ - Repubblica Ceca 3
GR - Grecia 3
KZ - Kazakistan 3
MA - Marocco 3
MY - Malesia 3
PR - Porto Rico 3
PY - Paraguay 3
TH - Thailandia 3
UZ - Uzbekistan 3
VE - Venezuela 3
AW - Aruba 2
AZ - Azerbaigian 2
BS - Bahamas 2
CI - Costa d'Avorio 2
EE - Estonia 2
GY - Guiana 2
KW - Kuwait 2
LB - Libano 2
LT - Lituania 2
RO - Romania 2
VG - Isole Vergini Britanniche 2
AI - Anguilla 1
BB - Barbados 1
BM - Bermuda 1
BY - Bielorussia 1
CG - Congo 1
DO - Repubblica Dominicana 1
ET - Etiopia 1
EU - Europa 1
GA - Gabon 1
GE - Georgia 1
HR - Croazia 1
LK - Sri Lanka 1
LY - Libia 1
NO - Norvegia 1
NZ - Nuova Zelanda 1
PA - Panama 1
PS - Palestinian Territory 1
SC - Seychelles 1
SN - Senegal 1
Totale 8.979
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Città #
Dallas 624
Ashburn 538
Singapore 488
San Jose 369
Chandler 327
Council Bluffs 188
Santa Clara 182
Trento 169
Columbus 146
Rome 141
Ann Arbor 133
Fairfield 109
Seoul 102
New York 98
Los Angeles 94
Beijing 81
Ho Chi Minh City 76
Milan 72
Princeton 72
Moscow 71
Riga 64
Hanoi 57
Lauterbourg 56
San Mateo 56
Phoenix 51
The Dalles 51
Hong Kong 49
Atlanta 48
Houston 44
Seattle 44
Helsinki 43
Wilmington 42
Chicago 41
Woodbridge 40
Dublin 39
Cambridge 38
Amsterdam 34
Buffalo 34
Orem 30
London 27
Toronto 26
Boardman 24
Sofia 24
Levico Terme 23
Brooklyn 20
Salt Lake City 20
San Diego 20
Washington 19
Munich 18
São Paulo 18
Verona 17
Riverside 16
Chennai 15
Lappeenranta 14
Montreal 14
North Bergen 14
Warsaw 14
Redondo Beach 13
Tokyo 13
Da Nang 12
Povo 12
Rio de Janeiro 12
Taipei 12
Tampa 12
Nuremberg 11
San Francisco 11
Stockholm 11
Frankfurt am Main 10
Mexico City 10
Boston 9
Falkenstein 9
Haiphong 9
Miano 9
Mumbai 9
Villaricca 9
Brescia 8
Denver 8
Guangzhou 8
Jakarta 8
Manchester 8
Memphis 8
Naples 8
Vienna 8
Hefei 7
Norwalk 7
Pune 7
Quito 7
Secaucus 7
Shanghai 7
Abu Dhabi 6
Andover 6
Ankara 6
Baghdad 6
Cagliari 6
Cincinnati 6
Guatemala City 6
Kilburn 6
Las Vegas 6
Providencia 6
San Antonio 6
Totale 5.649
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Nome #
Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound 406
Point of Care Image Analysis for COVID-19 276
Automatic Pleural Line Extraction and COVID-19 Scoring from Lung Ultrasound Data 270
Dependence of lung ultrasound vertical artifacts on frequency, bandwidth, focus and angle of incidence: An in vitro study 219
Synthetic Lung Ultrasound Data Generation Using Autoencoder with Generative Adversarial Network 190
Lung Ultrasound Spectroscopy Applied to the Differential Diagnosis of Pulmonary Diseases: an in vivo multicenter clinical study 184
Development of Lung Ultrasound Quantitative Approaches and Automatic Semi-Quantitative Strategies: In Silico, In Vitro, and Clinical Studies 174
Oversample minority classes in Lung Ultrasound using Generative Adversarial Network 172
Differential Diagnosis of Lung Disease through Quantitative Lung Ultrasound Spectroscopy, an in vivo clinical study over 114 patients 171
A Multicenter Study Assessing Artificial Intelligence Capability in Scoring Lung Ultrasound Videos of COVID-19 Patients 168
Lung Ultrasound in COVID-19 and Post-COVID-19 Patients, an Evidence-Based Approach 161
Assessment of COVID-19 in lung ultrasound by combining anatomy and sonographic artifacts using deep learning 159
Automated segmentation and scoring of lung ultrasound images of COVID-19 patients 157
Low-complexity lung ultrasound video scoring by means of intensity projection-based video compression 156
Benchmark methodological approach for the application of artificial intelligence to lung ultrasound data from COVID-19 patients: From frame to prognostic-level 155
Proposal for International Standardization of the Use of Lung Ultrasound for Patients With COVID-19 154
Deep learning applied to lung ultrasound videos for scoring COVID-19 patients: A multicenter study 154
Quantitative Lung Ultrasound Spectroscopy applied to the Diagnosis of Pulmonary Fibrosis: first clinical study 150
Application of Tensor Completion for Reducing the Beamforming Time in Ultrafast Ultrasound Imaging: A Doppler Ultrasound Assessment 147
Deep Learning-Based Classification of Reduced Lung Ultrasound Data from COVID-19 Patients 146
Time for a new international evidence-based recommendations for point-of-care lung ultrasound 140
Impact of pixel, intensity, & temporal resolution on automatic scoring of LUS from Coronavirus disease 2019 patients 140
A Novel Empirical Wavelet Transform Approach for Classification of Radiofrequency Lung Ultrasound Signals Applied to Diagnosis of Lung Diseases 136
Is there a role for lung ultrasound during the COVID-19 pandemic? 136
On Lung Ultrasound Patterns Specificity in the Management of COVID-19 Patients 130
Agreement between expert sonographers and artificial intelligence in the evaluation of lung ultrasound data acquired from COVID-19 patients 130
Lung Ultrasound for COVID-19 Patchy Pneumonia: Extended or Limited Evaluations? 129
Multi-objective automatic analysis of lung ultrasound data from COVID-19 patients by means of deep learning and decision trees 128
Quantitative Lung Ultrasound Spectroscopy Classification Performance in Differentiating CPE, Pneumonia, and PF, a Comparative Classifiers’ Analysis 126
Differentiation of Pulmonary Fibrosis by Means of Quantitative Lung Ultrasound Spectroscopy, First Clinical Study in Humans 126
On the impact of pixel resolution on automated scoring of lung ultrasound images from coronavirus disease 2019 patients 125
Automatic Scoring of COVID-19 LUS Videos Using Cross-correlation-Based Features Aggregated from Frame-Level Confidence Levels Obtained by a Pre-trained Deep Neural Network 124
Multicenter Study on Lung Ultrasound COVID-19 and Post-COVID-19 Patients and On the Impact of Pixel Resolution on Automated Scoringof Lung Ultrasound Images From COVID-19 Patients 122
Integrating Domain Knowledge into Deep Networks for Lung Ultrasound with Applications to COVID-19 121
On the Impact of Different Lung Ultrasound Imaging Protocols in the Evaluation of Patients Affected by Coronavirus Disease 2019: How Many Acquisitions Are Needed? 120
Estimation of Lung Surface Roughness by Means of an Ultrasound Multifrequency Approach, in silico and in vitro results 119
Lung ultrasound and high-resolution CT-scan of the chest for COVID-19 pneumonia 118
Coronavirus disease 2019 patients prognostic stratification based on low complex lung ultrasound video compression 115
Alveolar Geometry Estimation Through Quantitative Lung Ultrasound Spectroscopy, Phantom Study with Monodisperse Vs Polydisperse Microbubble Populations 114
Numerical study on lung ultrasound B-line formation as a function of imaging frequency and alveolar geometries 114
The impact of B-lines' frequency characterization on lung ultrasound imaging, in vitro- and in vivo study 113
There is a Validated Acquisition Protocol for Lung Ultrasonography in COVID-19 Pneumonia 113
Quantitative lung ultrasound spectroscopy, an in vivo clinical study conducted over 101 patients 111
On the influence of imaging parameters on lung ultrasound B-line artifacts, in vitro study 110
Effect of Imaging Parameters on the Visualization of Lung Ultrasound B-line Artifacts 109
A standardised and evidenced-based lung ultrasound acquisition protocol and scoring system for the monitoring and stratification of COVID-19 and post-COVID-19 patients 106
Limiting the areas inspected by lung ultrasound leads to an underestimation of COVID-19 patients' condition 104
Impact of Frequency, Bandwidth, Focus, and Angle of Incidence on Lung Ultrasound Vertical Artifacts' Intensity, in-vitro Study 103
Human‐to‐AI Interrater Agreement for Lung Ultrasound Scoring in COVID‐19 Patients 99
LUS for COVID‐19 Pneumonia: Flexible or Reproducible Approach? 98
State of the Art in Lung Ultrasound, Shifting from Qualitative to Quantitative Analyses 97
Lung ultrasound patterns analysis at video and prognostic level in a resource-constrained setting 94
Ultrasound multifrequency strategy applied to the estimation of lung surface roughness 94
Novel Quantitative Lung Ultrasound Spectroscopy Approach for Diseases Classification 91
Neuro-symbolic interpretable AI for automatic COVID-19 patient-stratification based on standardised lung ultrasound data 87
Ultrasound Multifrequency Strategy To Estimate the Lung Surface Roughness, In Silico and In Vitro Results 86
Automatically Scoring Lung Ultrasound Videos of COVID-19 and post-COVID-19 Patients 86
Investigating training-test data splitting strategies for automated segmentation and scoring of COVID-19 lung ultrasound images 86
Investigating the link between intensity of lung ultrasound vertical artifacts and penetration depth of ultrasound waves, in silico study 85
Quantitative lung ultrasound spectroscopy: First comparison with gold standard computed tomography scan and standard lung ultrasound for diagnosis of pneumonia versus cardiogenic pulmonary edema 84
Ultrasound waves propagation in aerated inhomogeneous media 80
Multi-Frequency Approach to Estimate the Roughness of Lung Surface, in silico Study 77
Iterative Deconvolution Approach for Automatic Segmentation of Lung Ultrasound Vertical Artifacts 77
On the interception of the optimal imaging plane for pleural line scanning with automatic robot assisted lung ultrasound: An experimental study 75
Neuro-symbolic interpretable AI for automatic COVID-19 patient-stratification based on standardised lung ultrasound data 71
Corrigendum to “Fully automated quantitative lung ultrasound spectroscopy for the differential diagnosis of lung diseases: The first multicenter in-vivo clinical study”(Computers in Biology and Medicine, (2026), 200, C, (111365), (S0010482525017196), 10.1016/j.compbiomed.2025.111365) 66
Novel Quantitative Lung Ultrasound Spectroscopy Approach to differentiate Acute Exacerbation of Pulmonary Fibrosis from Pulmonary Fibrosis – preliminary results from SAURON Study 57
Fully automated Quantitative Lung Ultrasound spectroscopy for the differential diagnosis of lung diseases: The first multicenter in-vivo clinical study 56
Lung ultrasound video scoring using a novel motion-aware segmentation technique: Toward automated neonatal LUS scoring 50
Quantitative lung ultrasound spectroscopy: a novel approach to differentiate acute exacerbation due to pulmonary emphysema versus pulmonary fibrosis – preliminary results from SAURON Study 50
4-Dimensional lung ultrasound imaging for lung surface motion estimation: an in vivo feasibility study 45
Novel velocity model for the quantitative characterization of pleural sliding, in vivo multicenter clinical study on RF lung ultrasound data 29
4-Dimensional lung ultrasound imaging for lung surface motion estimation: An in vivo feasibility study 28
Quantitative lung ultrasound spectroscopy versus computed tomography: A comparative study to differentiate pneumonia and cardiogenic pulmonary edema 27
Quantitative Lung Ultrasound Biomarkers for Automatic Stratification of Idiopathic Pulmonary Fibrosis: an in-vivo study 27
A first clinical study on the quantitative characterization of pleural sliding using multifrequency lung ultrasound in-vivo data 25
On the optimization of pleural line scanning through automatic robot assisted lung ultrasound, an experimental study 24
Quantitative Assessment of Pleural Sliding Velocity using Lung Ultrasound Spectroscopy: First Clinical Study on in-vivo Radio-Frequency Data 23
Physics-informed vessel characterization and compliance scoring in ultrasound localization microscopy 21
Real-time and automatic lung diagnostics by quantitative lung ultrasound spectroscopy, a multicenter study 20
Impact of media filling acoustic traps on the spectral characterization of lung ultrasound vertical artifacts, an experimental study 18
Multicenter clinical study on pleural sliding quantitative characterization by means of multifrequency lung ultrasound 18
Lung ultrasound and high-resolution CT-scan of the chest for COVID-19 pneumonia 2
A novel methodology to characterize pleural sliding: first multicenter clinical study using radio frequency lung ultrasound data 2
Totale 9.206
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Categoria #
all - tutte 39.994
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 39.994
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Totale Lug Ago Sett Ott Nov Dic Gen Feb Mar Apr Mag Giu
2021/2022364 0 0 0 11 62 25 8 110 19 43 23 63
2022/2023693 65 44 13 74 92 119 4 80 101 12 63 26
2023/2024399 27 35 42 19 60 91 23 30 1 22 9 40
2024/20251.285 26 5 88 167 75 162 52 62 157 250 142 99
2025/20264.168 274 422 731 425 386 224 535 104 402 274 198 193
2026/20271.788 260 408 355 765 0 0 0 0 0 0 0 0
Totale 9.206