Artificial Intelligence and Network Medicine: Path to Precision Medicine
Over the past two decades, network medicine (NM) has evolved to help define disease mechanisms, identify drug targets, and guide increasingly precise therapies. In recent years, the integration of NM with artificial intelligence (AI), particularly deep learning techniques, has evolved with increasing applications. AI techniques help elucidate complex disease mechanisms and define precise therapies. The depth of useful, mechanistic information implicit in molecular interaction networks and prior deep learning successes provide a rational basis for combining NM and AI in the analyses of large multiomic datasets to enhance the speed, predictive precision, and biological insights of the computational process. In this review, we provide a summary of concepts related to the combined use of AI and NM as a path to precision medicine, illustrating the success of this joint approach to biomedical complexity and its ongoing challenges.
Authors
- Lina Badimón (ORCID: https://orcid.org/0000-0002-9162-2459)
- Feixiong Cheng (ORCID: https://orcid.org/0000-0002-1736-2847)
- Rajat M. Gupta (ORCID: https://orcid.org/0000-0001-9865-4106)
- Jörg Menche (ORCID: https://orcid.org/0000-0002-1583-6404)
- Joseph Loscalzo (ORCID: https://orcid.org/0000-0002-1153-8047)
- Jean‐Luc Balligand (ORCID: https://orcid.org/0000-0002-0522-4156)
- Yang‐Yu Liu (ORCID: https://orcid.org/0000-0003-2728-4907)
- Lucia Altucci (ORCID: https://orcid.org/0000-0002-7312-5387)
- Giulia Menichetti (ORCID: https://orcid.org/0000-0001-5201-6774)
- Marcus Hacker (ORCID: https://orcid.org/0000-0002-4222-4083)
- Dawn L. DeMeo (ORCID: https://orcid.org/0000-0001-9653-0636)
- Harald H.H.W. Schmidt (ORCID: https://orcid.org/0000-0003-0419-5549)
- Paolo Parini (ORCID: https://orcid.org/0000-0002-6541-8542)
- Jan Baumbach (ORCID: https://orcid.org/0000-0002-0282-0462)
- Sabrina Maniscalco (ORCID: https://orcid.org/0000-0001-8559-0828)
- Marinka Žitnik (ORCID: https://orcid.org/0000-0001-8530-7228)
- Alberico L. Catapano (ORCID: https://orcid.org/0000-0002-7593-2094)
Institutions
- Brigham and Women's Hospital (US)
- Northeastern University (US)
- University of Vienna (AT)
- Cleveland Clinic (US)
- Karolinska University Hospital (SE)
- University of Helsinki (FI)
- Harvard University (US)
- Austrian Academy of Sciences (AT)
- Universität Hamburg (DE)
- University of Campania "Luigi Vanvitelli" (IT)
- Max Perutz Labs (AT)
- Maastricht University (NL)
- Cleveland Clinic Lerner College of Medicine (US)
- MultiMedica (IT)
- Ludwig Boltzmann Institute for Age Research (AT)
- CeMM Research Center for Molecular Medicine (AT)
- Cardiovascular Research Center (BR)
- Dana-Farber/Harvard Cancer Center (US)
- Ludwig Boltzmann Institute Applied Diagnostics (AT)
- Ludwig Boltzmann Institute for Cancer Research (AT)
- Guided Therapeutics (United States) (US)
- Artificial Intelligence in Medicine (Canada) (CA)
- Case Western Reserve University (US)
- Medical University of Vienna (AT)
- UCLouvain (BE)
Publication Details
- Journal
- NEJM AI
- Published
- 2025-08-28
- DOI
- https://doi.org/10.1056/aira2401229
- Citations
- 2
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 3.01