IRIS
Mento, Federico
 Distribuzione geografica
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Continente #
NA - Nord America 3.367
AS - Asia 1.718
EU - Europa 1.350
SA - Sud America 292
AF - Africa 35
OC - Oceania 3
Continente sconosciuto - Info sul continente non disponibili 1
Totale 6.766
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Nazione #
US - Stati Uniti d'America 3.307
SG - Singapore 780
IT - Italia 544
CN - Cina 324
VN - Vietnam 242
BR - Brasile 237
RU - Federazione Russa 192
KR - Corea 106
FR - Francia 87
GB - Regno Unito 79
DE - Germania 67
SE - Svezia 66
FI - Finlandia 64
IN - India 64
LV - Lettonia 64
HK - Hong Kong 55
NL - Olanda 54
IE - Irlanda 38
CA - Canada 32
BG - Bulgaria 24
MX - Messico 19
AR - Argentina 17
TR - Turchia 16
AT - Austria 15
BD - Bangladesh 15
ID - Indonesia 15
IQ - Iraq 15
PL - Polonia 14
TW - Taiwan 13
ES - Italia 12
JP - Giappone 12
CL - Cile 11
PK - Pakistan 9
ZA - Sudafrica 9
AE - Emirati Arabi Uniti 8
EC - Ecuador 8
UA - Ucraina 8
SA - Arabia Saudita 7
JO - Giordania 6
PE - Perù 6
PH - Filippine 6
DZ - Algeria 5
EG - Egitto 5
KE - Kenya 5
CH - Svizzera 4
DK - Danimarca 4
OM - Oman 4
CZ - Repubblica Ceca 3
GR - Grecia 3
MA - Marocco 3
MY - Malesia 3
NP - Nepal 3
PY - Paraguay 3
TH - Thailandia 3
UY - Uruguay 3
UZ - Uzbekistan 3
VE - Venezuela 3
AU - Australia 2
AZ - Azerbaigian 2
BE - Belgio 2
CI - Costa d'Avorio 2
CO - Colombia 2
GY - Guiana 2
JM - Giamaica 2
KW - Kuwait 2
RO - Romania 2
BB - Barbados 1
CG - Congo 1
CR - Costa Rica 1
DO - Repubblica Dominicana 1
ET - Etiopia 1
EU - Europa 1
GA - Gabon 1
GE - Georgia 1
GT - Guatemala 1
HN - Honduras 1
HR - Croazia 1
IL - Israele 1
KZ - Kazakistan 1
LB - Libano 1
LK - Sri Lanka 1
LT - Lituania 1
LY - Libia 1
NO - Norvegia 1
NZ - Nuova Zelanda 1
PA - Panama 1
PT - Portogallo 1
SN - Senegal 1
TG - Togo 1
VG - Isole Vergini Britanniche 1
Totale 6.766
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Città #
Dallas 615
Singapore 479
Chandler 327
Ashburn 297
San Jose 218
Ann Arbor 133
Santa Clara 133
Trento 129
Rome 121
Fairfield 109
Columbus 106
Seoul 102
Ho Chi Minh City 76
Beijing 73
New York 73
Princeton 72
Moscow 71
Los Angeles 68
Riga 64
Hanoi 57
Lauterbourg 56
San Mateo 56
Hong Kong 45
Council Bluffs 44
Helsinki 43
Seattle 43
Woodbridge 40
Houston 39
The Dalles 39
Cambridge 38
Wilmington 38
Dublin 37
Amsterdam 34
Chicago 32
Orem 28
Sofia 24
London 23
Buffalo 21
Salt Lake City 19
San Diego 19
Munich 18
Milan 17
São Paulo 16
Chennai 15
Lappeenranta 14
Redondo Beach 13
Warsaw 13
Da Nang 12
Povo 12
Taipei 12
Toronto 12
Verona 12
Rio de Janeiro 11
Stockholm 11
Tokyo 11
Washington 11
Boardman 10
Brooklyn 10
Frankfurt am Main 10
Montreal 10
Nuremberg 10
Falkenstein 9
Haiphong 9
San Francisco 9
Tampa 9
Villaricca 9
Boston 8
Brescia 8
Guangzhou 8
Jakarta 8
Vienna 8
Hefei 7
Manchester 7
Mexico City 7
Norwalk 7
Phoenix 7
Pune 7
Abu Dhabi 6
Andover 6
Ankara 6
Atlanta 6
Baghdad 6
Denver 6
Kilburn 6
Mumbai 6
Providencia 6
Shenzhen 6
Turku 6
Xingtai 6
Curitiba 5
Falls Church 5
Johannesburg 5
Lawrence 5
Paris 5
Shanghai 5
Xi'an 5
Amman 4
Belo Horizonte 4
Brasília 4
Cagliari 4
Totale 4.551
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Nome #
Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound 339
Automatic Pleural Line Extraction and COVID-19 Scoring from Lung Ultrasound Data 242
Synthetic Lung Ultrasound Data Generation Using Autoencoder with Generative Adversarial Network 150
A Multicenter Study Assessing Artificial Intelligence Capability in Scoring Lung Ultrasound Videos of COVID-19 Patients 149
Oversample minority classes in Lung Ultrasound using Generative Adversarial Network 146
Differential Diagnosis of Lung Disease through Quantitative Lung Ultrasound Spectroscopy, an in vivo clinical study over 114 patients 145
Automated segmentation and scoring of lung ultrasound images of COVID-19 patients 143
Assessment of COVID-19 in lung ultrasound by combining anatomy and sonographic artifacts using deep learning 142
Lung Ultrasound in COVID-19 and Post-COVID-19 Patients, an Evidence-Based Approach 139
Proposal for International Standardization of the Use of Lung Ultrasound for Patients With COVID-19 132
Development of Lung Ultrasound Quantitative Approaches and Automatic Semi-Quantitative Strategies: In Silico, In Vitro, and Clinical Studies 131
Impact of pixel, intensity, & temporal resolution on automatic scoring of LUS from Coronavirus disease 2019 patients 127
Deep learning applied to lung ultrasound videos for scoring COVID-19 patients: A multicenter study 126
Time for a new international evidence-based recommendations for point-of-care lung ultrasound 125
Application of Tensor Completion for Reducing the Beamforming Time in Ultrafast Ultrasound Imaging: A Doppler Ultrasound Assessment 123
Quantitative Lung Ultrasound Spectroscopy applied to the Diagnosis of Pulmonary Fibrosis: first clinical study 122
Deep Learning-Based Classification of Reduced Lung Ultrasound Data from COVID-19 Patients 120
Agreement between expert sonographers and artificial intelligence in the evaluation of lung ultrasound data acquired from COVID-19 patients 117
Is there a role for lung ultrasound during the COVID-19 pandemic? 115
On Lung Ultrasound Patterns Specificity in the Management of COVID-19 Patients 115
Lung Ultrasound Spectroscopy Applied to the Differential Diagnosis of Pulmonary Diseases: an in vivo multicenter clinical study 115
Benchmark methodological approach for the application of artificial intelligence to lung ultrasound data from COVID-19 patients: From frame to prognostic-level 113
Differentiation of Pulmonary Fibrosis by Means of Quantitative Lung Ultrasound Spectroscopy, First Clinical Study in Humans 113
Low-complexity lung ultrasound video scoring by means of intensity projection-based video compression 110
On the impact of pixel resolution on automated scoring of lung ultrasound images from coronavirus disease 2019 patients 110
A Novel Empirical Wavelet Transform Approach for Classification of Radiofrequency Lung Ultrasound Signals Applied to Diagnosis of Lung Diseases 109
Quantitative Lung Ultrasound Spectroscopy Classification Performance in Differentiating CPE, Pneumonia, and PF, a Comparative Classifiers’ Analysis 109
Lung Ultrasound for COVID-19 Patchy Pneumonia: Extended or Limited Evaluations? 108
Estimation of Lung Surface Roughness by Means of an Ultrasound Multifrequency Approach, in silico and in vitro results 107
On the Impact of Different Lung Ultrasound Imaging Protocols in the Evaluation of Patients Affected by Coronavirus Disease 2019: How Many Acquisitions Are Needed? 107
Multi-objective automatic analysis of lung ultrasound data from COVID-19 patients by means of deep learning and decision trees 106
Integrating Domain Knowledge into Deep Networks for Lung Ultrasound with Applications to COVID-19 106
Lung ultrasound and high-resolution CT-scan of the chest for COVID-19 pneumonia 105
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 99
There is a Validated Acquisition Protocol for Lung Ultrasonography in COVID-19 Pneumonia 99
Dependence of lung ultrasound vertical artifacts on frequency, bandwidth, focus and angle of incidence: An in vitro study 98
On the influence of imaging parameters on lung ultrasound B-line artifacts, in vitro study 96
The impact of B-lines' frequency characterization on lung ultrasound imaging, in vitro- and in vivo study 96
Point of Care Image Analysis for COVID-19 95
Effect of Imaging Parameters on the Visualization of Lung Ultrasound B-line Artifacts 94
Coronavirus disease 2019 patients prognostic stratification based on low complex lung ultrasound video compression 93
Alveolar Geometry Estimation Through Quantitative Lung Ultrasound Spectroscopy, Phantom Study with Monodisperse Vs Polydisperse Microbubble Populations 93
LUS for COVID‐19 Pneumonia: Flexible or Reproducible Approach? 92
Limiting the areas inspected by lung ultrasound leads to an underestimation of COVID-19 patients' condition 91
Numerical study on lung ultrasound B-line formation as a function of imaging frequency and alveolar geometries 90
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 87
Quantitative lung ultrasound spectroscopy, an in vivo clinical study conducted over 101 patients 86
Impact of Frequency, Bandwidth, Focus, and Angle of Incidence on Lung Ultrasound Vertical Artifacts' Intensity, in-vitro Study 86
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 86
Human‐to‐AI Interrater Agreement for Lung Ultrasound Scoring in COVID‐19 Patients 85
State of the Art in Lung Ultrasound, Shifting from Qualitative to Quantitative Analyses 80
Ultrasound multifrequency strategy applied to the estimation of lung surface roughness 76
Neuro-symbolic interpretable AI for automatic COVID-19 patient-stratification based on standardised lung ultrasound data 76
Lung ultrasound patterns analysis at video and prognostic level in a resource-constrained setting 75
Investigating the link between intensity of lung ultrasound vertical artifacts and penetration depth of ultrasound waves, in silico study 75
Ultrasound Multifrequency Strategy To Estimate the Lung Surface Roughness, In Silico and In Vitro Results 69
Automatically Scoring Lung Ultrasound Videos of COVID-19 and post-COVID-19 Patients 69
Investigating training-test data splitting strategies for automated segmentation and scoring of COVID-19 lung ultrasound images 64
Novel Quantitative Lung Ultrasound Spectroscopy Approach for Diseases Classification 60
Iterative Deconvolution Approach for Automatic Segmentation of Lung Ultrasound Vertical Artifacts 59
Ultrasound waves propagation in aerated inhomogeneous media 59
Multi-Frequency Approach to Estimate the Roughness of Lung Surface, in silico Study 54
Neuro-symbolic interpretable AI for automatic COVID-19 patient-stratification based on standardised lung ultrasound data 50
Novel Quantitative Lung Ultrasound Spectroscopy Approach to differentiate Acute Exacerbation of Pulmonary Fibrosis from Pulmonary Fibrosis – preliminary results from SAURON Study 40
Quantitative lung ultrasound spectroscopy: a novel approach to differentiate acute exacerbation due to pulmonary emphysema versus pulmonary fibrosis – preliminary results from SAURON Study 33
Lung ultrasound video scoring using a novel motion-aware segmentation technique: Toward automated neonatal LUS scoring 32
Fully automated Quantitative Lung Ultrasound spectroscopy for the differential diagnosis of lung diseases: The first multicenter in-vivo clinical study 29
4-Dimensional lung ultrasound imaging for lung surface motion estimation: an in vivo feasibility study 18
On the interception of the optimal imaging plane for pleural line scanning with automatic robot assisted lung ultrasound: An experimental study 10
Corrigendum to “Fully automated quantitative lung ultrasound spectroscopy for the differential diagnosis of lung diseases: The first multicenter in-vivo clinical study” [Comput. Biol. Med. (200), 1 January 2026, 111365] 9
Totale 6.969
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Categoria #
all - tutte 31.293
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 31.293
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Totale Lug Ago Sett Ott Nov Dic Gen Feb Mar Apr Mag Giu
2020/2021133 0 0 0 0 0 0 0 0 0 55 68 10
2021/2022430 15 50 1 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
2025/20263.719 274 422 731 425 386 224 535 104 402 216 0 0
Totale 6.969