Jurman, Giuseppe
 Distribuzione geografica
Continente #
NA - Nord America 245
EU - Europa 111
AS - Asia 31
SA - Sud America 9
AF - Africa 5
Totale 401
Nazione #
US - Stati Uniti d'America 244
IT - Italia 61
CN - Cina 17
FR - Francia 17
BE - Belgio 11
DE - Germania 9
BR - Brasile 8
VN - Vietnam 7
GB - Regno Unito 3
UG - Uganda 3
ES - Italia 2
HK - Hong Kong 2
NL - Olanda 2
SG - Singapore 2
UA - Ucraina 2
CL - Cile 1
FI - Finlandia 1
GH - Ghana 1
IN - India 1
LV - Lettonia 1
MX - Messico 1
RU - Federazione Russa 1
SA - Arabia Saudita 1
SC - Seychelles 1
SE - Svezia 1
TW - Taiwan 1
Totale 401
Città #
Ashburn 33
Fairfield 32
Trento 21
Woodbridge 20
Seattle 18
Santa Cruz 16
Houston 15
Buffalo 13
Brussels 11
Cambridge 8
Wilmington 8
Las Vegas 7
Los Angeles 7
Guangzhou 6
Ann Arbor 4
Boardman 4
Dong Ket 4
Rome 4
San Diego 4
Chicago 3
Kampala 3
Mirano 3
Mountain View 3
Trieste 3
Brescia 2
Brignano Gera D'adda 2
Catania 2
Cedar Knolls 2
Central 2
Fontanafredda 2
Milan 2
Paris 2
Saltara 2
San Francisco 2
Shanghai 2
Udine 2
Venice 2
Wuhan 2
Amsterdam 1
Bari 1
Beijing 1
Bremen 1
Bristol 1
Cagliari 1
Cuauhtemoc 1
Dallas 1
Des Moines 1
Easton 1
Edinburgh 1
Grenoble 1
Hanoi 1
Helsinki 1
Jersey City 1
Kirkland 1
Mahé 1
Mumbai 1
Munich 1
Notre Dame 1
Oak Lawn 1
Phoenix 1
Provo 1
Riga 1
Riva 1
Riyadh 1
Rochester 1
Saarbrücken 1
Schio 1
Secaucus 1
Stockholm 1
Sunnyvale 1
Taipei 1
Torino 1
Turin 1
Vaprio d'Adda 1
Vigo 1
Totale 315
Nome #
Phylogenetic convolutional neural networks in metagenomics, file e3835195-25ab-72ef-e053-3705fe0ad821 206
Evaluating reproducibility of AI algorithms in digital pathology with DAPPER, file e3835197-297b-72ef-e053-3705fe0ad821 88
Precipitation Nowcasting with Orographic Enhanced Stacked Generalization: Improving Deep Learning Predictions on Extreme Events, file e3835196-8afe-72ef-e053-3705fe0ad821 48
Integrative Network Fusion: A Multi-Omics Approach in Molecular Profiling, file e3835197-9b21-72ef-e053-3705fe0ad821 37
An Invitation to Greater Use of Matthews Correlation Coefficient in Robotics and Artificial Intelligence, file e3835199-f566-72ef-e053-3705fe0ad821 20
Quantification of the Immune Content in Neuroblastoma: Deep Learning and Topological Data Analysis in Digital Pathology, file e3835199-e815-72ef-e053-3705fe0ad821 3
Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone, file e3835199-bd35-72ef-e053-3705fe0ad821 2
Quotients of maximal class of thin Lie algebras. The case of characteristic two, file e3835199-9d04-72ef-e053-3705fe0ad821 1
The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation, file e3835199-a20b-72ef-e053-3705fe0ad821 1
The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation, file e3835199-b06c-72ef-e053-3705fe0ad821 1
The Matthews Correlation Coefficient (MCC) is More Informative Than Cohen's Kappa and Brier Score in Binary Classification Assessment, file e3835199-b06d-72ef-e053-3705fe0ad821 1
Predictability of drug-induced liver injury by machine learning, file e3835199-c102-72ef-e053-3705fe0ad821 1
Predictability of drug-induced liver injury by machine learning, file e3835199-c236-72ef-e053-3705fe0ad821 1
Deep learning for automatic stereotypical motor movement detection using wearable sensors in autism spectrum disorders, file e3835199-c237-72ef-e053-3705fe0ad821 1
Machine learning models for predicting endocrine disruption potential of environmental chemicals, file e3835199-d26f-72ef-e053-3705fe0ad821 1
Predictability of drug-induced liver injury by machine learning, file e3835199-d270-72ef-e053-3705fe0ad821 1
The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation, file e3835199-e816-72ef-e053-3705fe0ad821 1
Totale 414
Categoria #
all - tutte 1.743
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 1.743


Totale Lug Ago Sett Ott Nov Dic Gen Feb Mar Apr Mag Giu
2018/201916 0 0 0 0 0 0 0 0 0 0 8 8
2019/202075 11 9 6 4 4 13 4 5 9 3 3 4
2020/202168 3 4 5 2 6 5 8 0 3 13 8 11
2021/202294 5 5 6 5 5 2 7 7 6 4 38 4
2022/202373 5 1 15 9 5 1 4 3 2 10 6 12
2023/202483 4 2 11 9 12 12 6 16 6 5 0 0
Totale 414