Nicole Bussola
Nicole Bussola
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Evaluating reproducibility of AI algorithms in digital pathology with DAPPER
A Bizzego, N Bussola, M Chierici, V Maggio, M Francescatto, L Cima, ...
PLoS computational biology 15 (3), e1006269, 2019
Integrating deep and radiomics features in cancer bioimaging
A Bizzego, N Bussola, D Salvalai, M Chierici, V Maggio, G Jurman, ...
2019 IEEE Conference on Computational Intelligence in Bioinformatics and …, 2019
Integrative network fusion: a multi-omics approach in molecular profiling
M Chierici, N Bussola, A Marcolini, M Francescatto, A Zandoną, ...
Frontiers in oncology 10, 1065, 2020
Predictability of drug-induced liver injury by machine learning
M Chierici, M Francescatto, N Bussola, G Jurman, C Furlanello
Biology direct 15 (1), 1-10, 2020
AI slipping on tiles: Data leakage in digital pathology
N Bussola, A Marcolini, V Maggio, G Jurman, C Furlanello
Pattern Recognition. ICPR International Workshops and Challenges: Virtual …, 2021
Towards a scientific blockchain framework for reproducible data analysis
C Furlanello, M De Domenico, G Jurman, N Bussola
arXiv preprint arXiv:1707.06552, 2017
Machine learning models for predicting endocrine disruption potential of environmental chemicals
M Chierici, M Giulini, N Bussola, G Jurman, C Furlanello
Journal of Environmental Science and Health, Part C 36 (4), 237-251, 2018
Quantification of the immune content in neuroblastoma: Deep learning and topological data analysis in digital pathology
N Bussola, B Papa, O Melaiu, A Castellano, D Fruci, G Jurman
International journal of molecular sciences 22 (16), 8804, 2021
histolab: A Python library for reproducible Digital Pathology preprocessing with automated testing
A Marcolini, N Bussola, E Arbitrio, M Amgad, G Jurman, C Furlanello
SoftwareX 20, 101237, 2022
Cyst segmentation on kidney tubules by means of U-Net deep-learning models
S Monaco, N Bussola, S Butto, D Sona, D Apiletti, G Jurman, E Viola, ...
2021 IEEE International Conference on Big Data (Big Data), 3923-3926, 2021
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