Advancing Toward P6 Medicine: Recommendations for Integrating Artificial Intelligence in Internal Medicine
The panel unanimously considered AI in Internal Medicine as an opportunity, achieving a complete consensus on the matter. AI-driven solutions, including clinical applications of GAI and DTx, hold the potential to strongly change internal medicine by streamlining workflows, enhancing patient care and generating valuable data.
Authors
- Carlo Drago (ORCID: https://orcid.org/0000-0002-3920-0267)
- Tiffany I. Leung (ORCID: https://orcid.org/0000-0002-6007-4023)
- Marco Montagna (ORCID: https://orcid.org/0000-0002-0907-7640)
- Filomena Pietrantonio (ORCID: https://orcid.org/0000-0003-1119-0869)
- Alessandro Signorini (ORCID: https://orcid.org/0000-0002-9768-3252)
- Ricardo Gómez‐Huelgas (ORCID: https://orcid.org/0000-0002-9909-3555)
- Ismael Said-Criado (ORCID: https://orcid.org/0000-0003-4094-5343)
- Francesco Rosiello (ORCID: https://orcid.org/0000-0002-6532-1185)
- Antonio Vinci (ORCID: https://orcid.org/0000-0002-4915-7733)
- Oleg Missikoff
Institutions
- University of Rome Tor Vergata (IT)
- Vita-Salute San Raffaele University (IT)
- American University of Rome (IT)
- Southern Illinois University School of Medicine (US)
- ASL Roma (IT)
- Saint Camillus International University of Health and Medical Sciences (IT)
- European University of Rome (IT)
- Hospital Regional Universitario de Málaga (ES)
- University Niccolò Cusano (IT)
- Azienda Sanitaria Locale Roma 3 (IT)
- Complejo Hospitalario de Pontevedra (ES)
- Sapienza University of Rome (IT)
Publication Details
- Journal
- Clinics and Practice
- Published
- 2025-10-29
- DOI
- https://doi.org/10.3390/clinpract15110200
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65