The clinical application of artificial intelligence in cancer precision treatment
Abstract Background Artificial intelligence has made significant contributions to oncology through the availability of high-dimensional datasets and advances in computing and deep learning. Cancer precision medicine aims to optimize therapeutic outcomes and reduce side effects for individual cancer...
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| Format: | Article |
| Language: | English |
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BMC
2025-01-01
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| Series: | Journal of Translational Medicine |
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| Online Access: | https://doi.org/10.1186/s12967-025-06139-5 |
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| author | Jinyu Wang Ziyi Zeng Zehua Li Guangyue Liu Shunhong Zhang Chenchen Luo Saidi Hu Siran Wan Linyong Zhao |
| author_facet | Jinyu Wang Ziyi Zeng Zehua Li Guangyue Liu Shunhong Zhang Chenchen Luo Saidi Hu Siran Wan Linyong Zhao |
| author_sort | Jinyu Wang |
| collection | DOAJ |
| description | Abstract Background Artificial intelligence has made significant contributions to oncology through the availability of high-dimensional datasets and advances in computing and deep learning. Cancer precision medicine aims to optimize therapeutic outcomes and reduce side effects for individual cancer patients. However, a comprehensive review describing the impact of artificial intelligence on cancer precision medicine is lacking. Observations By collecting and integrating large volumes of data and applying it to clinical tasks across various algorithms and models, artificial intelligence plays a significant role in cancer precision medicine. Here, we describe the general principles of artificial intelligence, including machine learning and deep learning. We further summarize the latest developments in artificial intelligence applications in cancer precision medicine. In tumor precision treatment, artificial intelligence plays a crucial role in individualizing both conventional and emerging therapies. In specific fields, including target prediction, targeted drug generation, immunotherapy response prediction, neoantigen prediction, and identification of long non-coding RNA, artificial intelligence offers promising perspectives. Finally, we outline the current challenges and ethical issues in the field. Conclusions Recent clinical studies demonstrate that artificial intelligence is involved in cancer precision medicine and has the potential to benefit cancer healthcare, particularly by optimizing conventional therapies, emerging targeted therapies, and individual immunotherapies. This review aims to provide valuable resources to clinicians and researchers and encourage further investigation in this field. |
| format | Article |
| id | doaj-art-4620681341e644109449ef2838da1d01 |
| institution | Kabale University |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj-art-4620681341e644109449ef2838da1d012025-02-02T12:40:30ZengBMCJournal of Translational Medicine1479-58762025-01-0123111610.1186/s12967-025-06139-5The clinical application of artificial intelligence in cancer precision treatmentJinyu Wang0Ziyi Zeng1Zehua Li2Guangyue Liu3Shunhong Zhang4Chenchen Luo5Saidi Hu6Siran Wan7Linyong Zhao8Department of Medical Genetics, West China Second University Hospital, Sichuan UniversityKey Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of EducationDepartment of Plastic and Burn Surgery, West China Hospital, Sichuan UniversityDepartment of Anesthesiology, West China Hospital, Sichuan UniversityDepartment of Cardiology, Panzhihua Iron and Steel Group General HospitalDepartment of Outpatient Chengbei, the Affiliated Stomatological Hospital, Southwest Medical UniversityDepartment of Stomatology, Yaan people’s HospitalDepartment of Gynaecology and Obstetrics, Yaan people’s HospitalDepartment of General Surgery & Laboratory of Gastric Cancer, State Key Laboratory of Biotherapy / Collaborative Innovation Center of Biotherapy and Cancer Center, West China Hospital, Sichuan UniversityAbstract Background Artificial intelligence has made significant contributions to oncology through the availability of high-dimensional datasets and advances in computing and deep learning. Cancer precision medicine aims to optimize therapeutic outcomes and reduce side effects for individual cancer patients. However, a comprehensive review describing the impact of artificial intelligence on cancer precision medicine is lacking. Observations By collecting and integrating large volumes of data and applying it to clinical tasks across various algorithms and models, artificial intelligence plays a significant role in cancer precision medicine. Here, we describe the general principles of artificial intelligence, including machine learning and deep learning. We further summarize the latest developments in artificial intelligence applications in cancer precision medicine. In tumor precision treatment, artificial intelligence plays a crucial role in individualizing both conventional and emerging therapies. In specific fields, including target prediction, targeted drug generation, immunotherapy response prediction, neoantigen prediction, and identification of long non-coding RNA, artificial intelligence offers promising perspectives. Finally, we outline the current challenges and ethical issues in the field. Conclusions Recent clinical studies demonstrate that artificial intelligence is involved in cancer precision medicine and has the potential to benefit cancer healthcare, particularly by optimizing conventional therapies, emerging targeted therapies, and individual immunotherapies. This review aims to provide valuable resources to clinicians and researchers and encourage further investigation in this field.https://doi.org/10.1186/s12967-025-06139-5Solid tumorMachine learningDeep learningPrecision radiotherapyTargeted therapyImmunotherapy |
| spellingShingle | Jinyu Wang Ziyi Zeng Zehua Li Guangyue Liu Shunhong Zhang Chenchen Luo Saidi Hu Siran Wan Linyong Zhao The clinical application of artificial intelligence in cancer precision treatment Journal of Translational Medicine Solid tumor Machine learning Deep learning Precision radiotherapy Targeted therapy Immunotherapy |
| title | The clinical application of artificial intelligence in cancer precision treatment |
| title_full | The clinical application of artificial intelligence in cancer precision treatment |
| title_fullStr | The clinical application of artificial intelligence in cancer precision treatment |
| title_full_unstemmed | The clinical application of artificial intelligence in cancer precision treatment |
| title_short | The clinical application of artificial intelligence in cancer precision treatment |
| title_sort | clinical application of artificial intelligence in cancer precision treatment |
| topic | Solid tumor Machine learning Deep learning Precision radiotherapy Targeted therapy Immunotherapy |
| url | https://doi.org/10.1186/s12967-025-06139-5 |
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