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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2510.14194 |
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| _version_ | 1866911214005649408 |
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| author | Bender, Göktuğ Faraj, Samer Bhardwaj, Anand |
| author_facet | Bender, Göktuğ Faraj, Samer Bhardwaj, Anand |
| contents | Artificial intelligence (AI) has become increasingly central to precision medicine by enabling the integration and interpretation of multimodal data, yet implementation in clinical settings remains limited. This paper provides a scoping review of literature from 2019-2024 on the implementation of AI in precision medicine, identifying key barriers and enablers across data quality, clinical reliability, workflow integration, and governance. Through an ecosystem-based framework, we highlight the interdependent relationships shaping real-world translation and propose future directions to support trustworthy and sustainable implementation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_14194 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Implementation of AI in Precision Medicine Bender, Göktuğ Faraj, Samer Bhardwaj, Anand Artificial Intelligence Artificial intelligence (AI) has become increasingly central to precision medicine by enabling the integration and interpretation of multimodal data, yet implementation in clinical settings remains limited. This paper provides a scoping review of literature from 2019-2024 on the implementation of AI in precision medicine, identifying key barriers and enablers across data quality, clinical reliability, workflow integration, and governance. Through an ecosystem-based framework, we highlight the interdependent relationships shaping real-world translation and propose future directions to support trustworthy and sustainable implementation. |
| title | Implementation of AI in Precision Medicine |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2510.14194 |