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  The small numbers of medicine and the big numbers of artificial intelligence: a curated-data approach to appropriateness in laboratory medicine and coagulation

  Anna Mazzetto, Alessandro Camerotto

  15-04-2026

  https://doi.org/10.4081/btvb.2026.460

  150

  PDF: 40
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  Artificial intelligence, platelets and aspirin

  Giovanni de Gaetano

  15-03-2024

  https://doi.org/10.4081/btvb.2024.130

  893

  PDF: 310
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  Artificial intelligence and machine learning in hemostasis and thrombosis

  Paolo Gresele

  30-12-2023

  https://doi.org/10.4081/btvb.2023.105

  3661

  PDF: 721
• 

  Plasma fibrinogen levels and all-cause and cause-specific mortality in an Italian adult population: results from the Moli-sani study

  Roberta Parisi, Simona Costanzo, Romy de Laat-Kremers, Augusto Di Castelnuovo, Amalia De Curtis, Teresa Panzera, Mariarosaria Persichillo, Chiara Cerletti, Giovanni de Gaetano, Maria Benedetta Donati, Licia Iacoviello, Bas de Laat , for the Moli-sani Study Investigators

  27-01-2023

  https://doi.org/10.4081/btvb.2023.46

  2164

  PDF: 552

  APPENDIX: 185

• CO39 | Artificial intelligence in hemophilia management: challenging the need for experts G. Sottilotta¹, D. Megalizzi¹, F. Luise² | ¹UOSD Microcitemie - Emostasi e Trombosi. Grande Ospedale Metropolitano Bianchi-Melacrino-Morelli, Reggio Calabria; ²Laboratorio Analisi, Grande Ospedale Metropolitano Bianchi-Melacrino-Morelli, Reggio Calabria, Italy

  22-10-2025

  https://doi.org/10.4081/btvb.2025.246

  486

  PDF: 0
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  On the impact of generative artificial intelligence on peer review

  Giovanni de Gaetano, Chiara Cerletti, Augusto Di Castelnuovo

  03-03-2025

  https://doi.org/10.4081/btvb.2025.176

  1142

  PDF: 364
• 

  The evolution of hemostasis genetics: from monogenic disorders to complex traits. A historical perspective

  Augusto Di Castelnuovo

  01-07-2025

  https://doi.org/10.4081/btvb.2025.184

  1407

  PDF: 267
• 

  PO61 | RISK FACTORS FOR INTRACRANIAL HEMORRHAGE: AN UMBRELLA REVIEW TO INFORM MACHINE LEARNING PREDICTION MODELS IN GLIOMA PATIENTS RECEIVING ANTICOAGULATION T.A. Adeyemo, S. Greenley, F. Ware, W. Jones, A. Maraveyas, F. Haque | ¹Centre of Excellence for Data Science, Artificial Intelligence and Modelling DAIM, Faculty of Science and Engineering, University of Hull, UK; ²Hull York Medical School, Hull, UK; ³Academic Library Services, University of Hull, UK; ⁴NHS Humber Health Partnership, Hull, UK

  Società Italiana di Emostasi e Trombosi

  16-04-2026

  https://doi.org/10.4081/btvb.2026.552

  124

  PDF: 25
• 

  Preface to the 13^th International Conference on Thrombosis and Hemostasis Issues in Cancer, 2026

  Anna Falanga, Benjamin Brenner, Alok A. Khorana

  16-04-2026

  https://doi.org/10.4081/btvb.2026.479

  158

  PDF: 105
• 

  Executive summary of the SISET position paper on the management of antithrombotic therapy in left ventricular thrombus

  Emanuele Valeriani, Arianna Pannunzio, Danilo Menichelli, Domenico Prisco, Walter Ageno, Daniele Pastori, Pasquale Pignatelli

  16-12-2025

  https://doi.org/10.4081/btvb.2025.401

  289

  PDF: 71

  HTML: 23

• PO23 | Plasmic score applicability for the diagnosis of thrombotic microangiopathy associated with acquired ADAMTS13 deficiency in emergency settings at the hub laboratory of AUSL Romagna: state of the art and future prospects M. Olivieri¹, M. Rosetti¹, A. Clementoni¹, V. Marinucci¹, M. Monterosso¹, E. Massari¹, V. Polli¹, M. Zauli¹, V. Sambri² | ¹Clinical Pathology Unit; ²Unit of Microbiology, Area Hub Laboratory, Cesena, Italy

  22-10-2025

  https://doi.org/10.4081/btvb.2025.284

  521

  PDF: 0