Giuseppe Jurman

Giuseppe Jurman is a mathematician, with a PhD in Algebra, working at MPBA on various aspects of computational biology. His main research interests are statistical machine learning, mathematical modeling for high-throughtput data and network analysis. He is also an expert in scientific programming with Python and other computing languages.

1. Chicco, Davide; Tötsch, Niklas; Jurman, Giuseppe,
   The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation,
   in «BIODATA MINING»,
   vol. 14,
   n. 1,
   2021
2. Chicco, Davide; Jurman, Giuseppe,
   An ensemble learning approach for enhanced classification of patients with hepatitis and cirrhosis,
   in «IEEE ACCESS»,
   2021
   , pp. 1 -
   1
3. Bussola, Nicole; Marcolini, Alessia; Maggio, Valerio; Jurman, Giuseppe; Furlanello, Cesare,
   AI Slipping on Tiles: Data Leakage in Digital Pathology,
   Pattern Recognition. ICPR International Workshops and Challenges. ICPR 2021,
   Springer,
   2021
   , pp. 167 -
   182
4. Chicco, Davide; Jurman, Giuseppe,
   The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation,
   in «BMC GENOMICS»,
   vol. 21,
   n. 1,
   2020
   , pp. 6 -
5. Chicco, Davide; Jurman, Giuseppe,
   Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone,
   in «BMC MEDICAL INFORMATICS AND DECISION MAKING»,
   vol. 20,
   n. 1,
   2020
   , pp. 16 -
6. Chierici, Marco; Francescatto, Margherita; Bussola, Nicole; Jurman, Giuseppe; Furlanello, Cesare,
   Predictability of drug-induced liver injury by machine learning,
   in «BIOLOGY DIRECT»,
   vol. 15,
   n. 1,
   2020
7. Franch, Gabriele; Nerini, Daniele; Pendesini, Marta; Coviello, Luca; Jurman, Giuseppe; Furlanello, Cesare,
   Precipitation Nowcasting with Orographic Enhanced Stacked Generalization: Improving Deep Learning Predictions on Extreme Events,
   in «ATMOSPHERE»,
   vol. 11,
   n. 3,
   2020
   , pp. 267 -
8. Chierici, Marco; Bussola, Nicole; Marcolini, Alessia; Francescatto, Margherita; Zandonà, Alessandro; Trastulla, Lucia; Agostinelli, Claudio; Jurman, Giuseppe; Furlanello, Cesare,
   Integrative Network Fusion: a multi-omics approach in molecular profiling,
   in «FRONTIERS IN ONCOLOGY»,
   vol. 10,
   2020
   , pp. 1065 -
9. Saverio Sorrentino, Francesco; Jurman, Giuseppe; De Nadai, Katia; Campa, Claudio; Furlanello, Cesare; Parmeggiani, Francesco,
   Application of Artificial Intelligence in Targeting Retinal Diseases,
   in «CURRENT DRUG TARGETS»,
   vol. 21,
   n. 12,
   2020
10. Franch, Gabriele; Maggio, Valerio; Coviello, Luca; Pendesini, Marta; Jurman, Giuseppe; Furlanello, Cesare,
    TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting,
    in «SCIENTIFIC DATA»,
    vol. 7,
    n. 1,
    2020

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