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.

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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
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article

Artificial intelligence in genomics: improving detection of fusion genes in soft tissue sarcomas

Hasibullah Aminpoor, Muhammad Shah Zaib, Hasiba Karimi, Muhammad Khizar et al.
Annals of Medicine and Surgery
Sarcoma Diagnosis and Treatment
article

Artificial intelligence in genomics: improving detection of fusion genes in soft tissue sarcomas

Hasibullah Aminpoor, Muhammad Shah Zaib, Hasiba Karimi, Muhammad Khizar, Savera Ejaz
article en

Abstract

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.

Annals of Medicine and SurgeryVol. 88(1)
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)
Openalex Percentile: Top 43%
Sarcoma Diagnosis and Treatment
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Artificial intelligence in genomics: improving detection of fusion genes in soft tissue sarcomas — Hasibullah Aminpoor, Muhammad Shah Zaib, et al. · Annals of Medicine and Surgery (2025) | TGRS Research Map | TGRS