Michela Antonelli
Michela Antonelli
Verified email at
Cited by
Cited by
Attributes and predictors of long COVID
CH Sudre, B Murray, T Varsavsky, MS Graham, RS Penfold, RC Bowyer, ...
Nature medicine 27 (4), 626-631, 2021
Vaccine side-effects and SARS-CoV-2 infection after vaccination in users of the COVID Symptom Study app in the UK: a prospective observational study
C Menni, K Klaser, A May, L Polidori, J Capdevila, P Louca, CH Sudre, ...
The Lancet Infectious Diseases 21 (7), 939-949, 2021
A large annotated medical image dataset for the development and evaluation of segmentation algorithms
AL Simpson, M Antonelli, S Bakas, M Bilello, K Farahani, B Van Ginneken, ...
arXiv preprint arXiv:1902.09063, 2019
Risk factors and disease profile of post-vaccination SARS-CoV-2 infection in UK users of the COVID Symptom Study app: a prospective, community-based, nested, case-control study
M Antonelli, RS Penfold, J Merino, CH Sudre, E Molteni, S Berry, ...
The Lancet Infectious Diseases 22 (1), 43-55, 2022
Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B. 1.1. 7: an ecological study
MS Graham, CH Sudre, A May, M Antonelli, B Murray, T Varsavsky, ...
The Lancet Public Health 6 (5), e335-e345, 2021
Illness duration and symptom profile in symptomatic UK school-aged children tested for SARS-CoV-2
E Molteni, CH Sudre, LS Canas, SS Bhopal, RC Hughes, M Antonelli, ...
The Lancet Child & Adolescent Health 5 (10), 708-718, 2021
Symptom prevalence, duration, and risk of hospital admission in individuals infected with SARS-CoV-2 during periods of omicron and delta variant dominance: a prospective …
C Menni, AM Valdes, L Polidori, M Antonelli, S Penamakuri, A Nogal, ...
The Lancet 399 (10335), 1618-1624, 2022
Multiobjective evolutionary optimization of type-2 fuzzy rule-based systems for financial data classification
M Antonelli, D Bernardo, H Hagras, F Marcelloni
IEEE Transactions on Fuzzy Systems 25 (2), 249-264, 2016
Urban and social sensing for sustainable mobility in smart cities
G Anastasi, M Antonelli, A Bechini, S Brienza, E D'Andrea, ...
2013 Sustainable Internet and ICT for Sustainability (SustainIT), 1-4, 2013
Multi-objective evolutionary design of granular rule-based classifiers
M Antonelli, P Ducange, B Lazzerini, F Marcelloni
Granular Computing 1 (1), 37-58, 2016
The medical segmentation decathlon
M Antonelli, A Reinke, S Bakas, K Farahani, A Kopp-Schneider, ...
Nature communications 13 (1), 1-13, 2022
Genetic training instance selection in multiobjective evolutionary fuzzy systems: A coevolutionary approach
M Antonelli, P Ducange, F Marcelloni
IEEE Transactions on fuzzy systems 20 (2), 276-290, 2011
Learning concurrently partition granularities and rule bases of Mamdani fuzzy systems in a multi-objective evolutionary framework
M Antonelli, P Ducange, B Lazzerini, F Marcelloni
International Journal of Approximate Reasoning 50 (7), 1066-1080, 2009
A novel approach based on finite-state machines with fuzzy transitions for nonintrusive home appliance monitoring
P Ducange, F Marcelloni, M Antonelli
IEEE Transactions on Industrial Informatics 10 (2), 1185-1197, 2014
A fast and efficient multi-objective evolutionary learning scheme for fuzzy rule-based classifiers
M Antonelli, P Ducange, F Marcelloni
Information Sciences 283, 36-54, 2014
Whole-body MRI quantitative biomarkers are associated significantly with treatment response in patients with newly diagnosed symptomatic multiple myeloma following bortezomib …
A Latifoltojar, M Hall-Craggs, A Bainbridge, N Rabin, R Popat, A Rismani, ...
European radiology 27 (12), 5325-5336, 2017
Segmentation and reconstruction of the lung volume in CT images
M Antonelli, B Lazzerini, F Marcelloni
Proceedings of the 2005 ACM symposium on Applied computing, 255-259, 2005
Learning knowledge bases of multi-objective evolutionary fuzzy systems by simultaneously optimizing accuracy, complexity and partition integrity
M Antonelli, P Ducange, B Lazzerini, F Marcelloni
Soft Computing 15 (12), 2335-2354, 2011
Common limitations of image processing metrics: A picture story
A Reinke, M Eisenmann, MD Tizabi, CH Sudre, T Rädsch, M Antonelli, ...
arXiv preprint arXiv:2104.05642, 2021
Machine learning classifiers can predict Gleason pattern 4 prostate cancer with greater accuracy than experienced radiologists
M Antonelli, EW Johnston, N Dikaios, KK Cheung, HS Sidhu, MB Appayya, ...
European radiology 29 (9), 4754-4764, 2019
The system can't perform the operation now. Try again later.
Articles 1–20