Response to venom immunotherapy: Exploratory retrospective machine learning clustering analysis
Immunotherapy reduces allergic response, as shown by decreased wheal size and IgE level. The integration of SAM and machine learning enables robust analysis of clinical data, supporting personalized allergy management.
Authors
- Attilio Di Girolamo (ORCID: https://orcid.org/0000-0003-2416-4838)
- Nada Chaoul (ORCID: https://orcid.org/0000-0002-7844-7377)
- Marcello Albanesi (ORCID: https://orcid.org/0000-0001-7608-9572)
- Silvio Tafuri (ORCID: https://orcid.org/0000-0003-4194-0210)
- Stefano Palazzo (ORCID: https://orcid.org/0009-0008-7307-6993)
- Marco Cinquantasei
- Alessandro Cinquantasei
- Claudio Loconsole
- Mattia Cristallo (ORCID: https://orcid.org/0009-0002-8055-5892)
- Cataldo Piarulli
- Roberto Caldelli
- Francesco Pugliese
- Giulia Caffarella
- Marco Aprigliano
- Eustachio Nettis
Institutions
- Scuola Superiore Sant'Anna (IT)
- Azienda Universitaria Ospedaliera Consorziale - Policlinico Bari (IT)
- Consorzio Nazionale Interuniversitario per le Telecomunicazioni (IT)
- Mercatorum University (IT)
- Allergan (France) (FR)
- University of Bari Aldo Moro (IT)
- Polytechnic University of Bari (IT)
Publication Details
- Journal
- Journal of Allergy and Clinical Immunology Global
- Published
- 2026-01-29
- DOI
- https://doi.org/10.1016/j.jacig.2026.100651
- Primary Topic
- Venomous Animal Envenomation and Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00