Publications

1. Chierici, Marco; Giulini, Marco; Bussola, Nicole; Jurman, Giuseppe; Furlanello, Cesare,
   Machine learning models for predicting endocrine disruption potential of environmental chemicals,
   in «JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH. PART C, ENVIRONMENTAL CARCINOGENESIS & ECOTOXICOLOGY REVIEWS»,
   vol. 36,
   n. 4,
   2019
   , pp. 237 -
   251
2. Boldrini, Renata; De Pasquale Maria, Debora; Melaiu, Ombretta; Chierici, Marco; Jurman, Giuseppe; De Benedetti Maria, Chiara; Salfi Nunzio, C; Castellano, Aurora; Collini, Paola; Furlanello, Cesare; Pistoia, Vito; Cifaldi, Loredana; Terenziani, Monica; Fruci, Doriana,
   Tumor-infiltrating T cells and PD-L1 expression in childhood malignant extracranial germ-cell tumors,
   in «ONCOIMMUNOLOGY»,
   vol. 8,
   n. 2,
   2019
3. Alikadic, Azra; Pertot, Ilaria; Eccel, Emanuele; Dolci, Claudia; Zarbo, Calogero; Caffarra, Amelia; De Filippi, Riccardo; Furlanello, Cesare,
   The impact of climate change on grapevine phenology and the influence of altitude: A regional study,
   in «AGRICULTURAL AND FOREST METEOROLOGY»,
   vol. 271,
   2019
   , pp. 73 -
   82
4. Jurman, Giuseppe,
   Seasonal Linear Predictivity in National Football Championships,
   in «BIG DATA»,
   vol. 7,
   n. 1,
   2019
   , pp. 21 -
   34
5. Bizzego, Andrea; Bussola, Nicole; Chierici, Marco; Maggio, Valerio; Francescatto, Margherita; Cima, Luca; Cristoforetti, Marco; Jurman, Giuseppe; Furlanello, Cesare,
   Evaluating reproducibility of AI algorithms in digital pathology with DAPPER,
   in «PLOS COMPUTATIONAL BIOLOGY»,
   vol. 15,
   n. 3,
   2019
   , pp. e1006269 -
6. Wu, Leihong; Liu, Zhichao; Bera, Tanmay; Ding, Hongjian; Langley, Darryl A.; Jenkins-Barnes, Amy; Furlanello, Cesare; Maggio, Valerio; Tong, Weida; Xu, Joshua,
   A deep learning model to recognize food contaminating beetle species based on elytra fragments,
   in «COMPUTERS AND ELECTRONICS IN AGRICULTURE»,
   vol. 166,
   2019
   , pp. 105002 -
7. Stella, Massimo; Cristoforetti, Marco; De Domenico, Manlio,
   Influence of augmented humans in online interactions during voting events,
   in «PLOS ONE»,
   vol. 14,
   n. 5,
   2019
   , pp. e0214210 -
8. Jurman, Giuseppe; Filosi, Michele; Visintainer, Roberto; Riccadonna, Samantha; Furlanello, Cesare,
   Stability in GRN inference,
   Gene Regulatory Networks: Methods and Protocols, Methods in Molecular Biology,
   2019
   , pp. 323 -
   346
9. Bizzego, A.; Bussola, N.; Salvalai, D.; Chierici, M.; Maggio, V.; Jurman, G.; Furlanello, C.,
   Integrating deep and radiomics features in cancer bioimaging,
   Proceedings of 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB),
   2019
   , pp. 1-
   8
   , (2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB),
   Siena, Italy,
   9-11 July 2019)
10. Rinnert, Kurt; Cristoforetti, Marco,
    Deep Learning Approach to Track Reconstruction in the upgraded VELO,
    in «EPJ WEB OF CONFERENCES»
    Proceedings of the 23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018),
    vol.214,
    2019
    , pp. 06038-
    , (23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018),
    Sofia, Bulgaria,
    9-13 July 2018)

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