Artificial intelligence in genomics: improving detection of fusion genes in soft tissue sarcomas
The integration of artificial intelligence (AI) into clinical workflows for soft tissue sarcomas (STS) marks a major step forward in precision oncology. As diagnostic complexity grows, AI-driven genomics - particularly in detecting fusion genes - enhances sensitivity, speed, and accuracy, improving patient stratification and guiding targeted therapies. The convergence of AI with multi-omic datasets, including transcriptomic, epigenomic, and imaging data, offers a holistic view of sarcoma biology, enabling earlier detection and more personalized treatment. Achieving these benefits, however, requires global collaboration, standardized protocols, and continuous clinician education. Ultimately, AI's transformative potential in STS management depends not only on technological innovation but also on the establishment of robust frameworks for its clinical adoption.
Authors
- Hasibullah Aminpoor (ORCID: https://orcid.org/0000-0003-1817-7800)
- Muhammad Shah Zaib (ORCID: https://orcid.org/0000-0002-0086-4218)
- Hasiba Karimi (ORCID: https://orcid.org/0000-0002-7618-3849)
- Muhammad Khizar
- Savera Ejaz
Institutions
- Kabul University (AF)
- Bezmiâlem Vakıf Üniversitesi (TR)
- Kabul University of Medical Sciences Abu Ali Ibn Sina (AF)
- Shaheed Mohtarma Benazir Bhutto Medical University (PK)
- GGZ inGeest (NL)
- Georgian American University (GE)
Publication Details
- Journal
- Annals of Medicine and Surgery
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1097/ms9.0000000000004206
- Primary Topic
- Sarcoma Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00