The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Building the foundation for genomics in precision medicine
Open accessAbstract
Precision medicine has the potential to profoundly improve the practice of medicine. However, the advances required will take time to implement. Genetics is already being used to direct clinical decision-making and its contribution is likely to increase. To accelerate these advances, fundamental changes are needed in the infrastructure and mechanisms for data collection, storage and sharing. This will create a continuously learning health-care system with seamless cycling between clinical care and research. Patients must be educated about the benefits of sharing data. The building blocks for such a system are already forming and they will accelerate the adoption of precision medicine.
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ClinGen — The Clinical Genome Resource
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Cited by
The potential for artificial intelligence in healthcare
Davenport, T., & Kalakota, R. (2019) · Future Healthcare Journal · doi:10.7861/futurehosp.6-2-94 · Cited by 3,800
Precision medicine, AI, and the future of personalized health care
Johnson, K. B., Wei, W., Weeraratne, D., Frisse, M. E., Misulis, K., Rhee, K., Zhao, J., & Snowdon, J. L. (2021) · Clinical and Translational Science · doi:10.1111/cts.12884 · Cited by 1,854
Swarm Learning for decentralized and confidential clinical machine learning
Warnat-Herresthal, S., Schultze, H., Shastry, K. L., Manamohan, S., Mukherjee, S., Garg, V., Sarveswara, R., Händler, K., Pickkers, P., Aziz, N. A., et al. (2021) · Nature · doi:10.1038/s41586-021-03583-3 · Cited by 884
Patient-Derived Organoids Predict Chemoradiation Responses of Locally Advanced Rectal Cancer
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Improved polygenic prediction by Bayesian multiple regression on summary statistics
Lloyd-Jones, L. R., Zeng, J., Sidorenko, J., Yengo, L., Moser, G., Kemper, K. E., Wang, H., Zheng, Z., Magi, R., Esko, T., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12653-0 · Cited by 528
Metadata
- Authors
- Aronson, S. J., & Rehm, H. L.
- Venue
- Nature
- Published
- 2015-10
- Volume
- 526
- Issue
- 7573
- Pages
- 336-342
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W1958673254
- Cited by
- 492
- References
- 9
- FWCI
- 82.97
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
