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| Main Authors: | , , , , |
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| Format: | Recurso digital |
| Language: | English |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.17018632 |
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| _version_ | 1866901904698638336 |
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| author | Chunlei Wang Jie Cao Manzhi Xia Jianying Kang Jinlian Liang |
| author_facet | Chunlei Wang Jie Cao Manzhi Xia Jianying Kang Jinlian Liang |
| contents | <p>The integration of artificial intelligence (AI) into precision medicine has revolutionized healthcare by enhancing diagnostic accuracy, optimizing treatment strategies, and improving surgical outcomes. This paper explores the transformative potential of AI in precision medicine, with a focus on intelligent imaging analysis and surgical ecosystem innovation. AI-driven techniques, such as machine learning and deep learning, have demonstrated remarkable capabilities in analyzing medical images, enabling early and accurate disease detection, particularly in cancer and cardiovascular conditions. Additionally, AI has significantly advanced surgical precision through robotic-assisted procedures and augmented reality, reducing complications and improving patient recovery. The paper also highlights the integration of diverse data sources, including genomics and wearable sensors, to provide comprehensive patient insights. Despite these advancements, challenges such as ethical considerations, data privacy, and algorithmic bias remain critical barriers to widespread adoption. The paper concludes by emphasizing the need for interdisciplinary collaboration, robust validation, and regulatory oversight to fully realize the potential of AI in precision medicine. By addressing these challenges, AI-powered precision medicine holds immense promise for delivering personalized, efficient, and equitable healthcare solutions.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17018632 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | AI-Powered Precision Medicine: Transforming Healthcare through Intelligent Imaging and Surgical Ecosystem Innovation Chunlei Wang Jie Cao Manzhi Xia Jianying Kang Jinlian Liang Artificial Intelligence Precision Medicine Medical Imaging Surgical Innovation Data Integration <p>The integration of artificial intelligence (AI) into precision medicine has revolutionized healthcare by enhancing diagnostic accuracy, optimizing treatment strategies, and improving surgical outcomes. This paper explores the transformative potential of AI in precision medicine, with a focus on intelligent imaging analysis and surgical ecosystem innovation. AI-driven techniques, such as machine learning and deep learning, have demonstrated remarkable capabilities in analyzing medical images, enabling early and accurate disease detection, particularly in cancer and cardiovascular conditions. Additionally, AI has significantly advanced surgical precision through robotic-assisted procedures and augmented reality, reducing complications and improving patient recovery. The paper also highlights the integration of diverse data sources, including genomics and wearable sensors, to provide comprehensive patient insights. Despite these advancements, challenges such as ethical considerations, data privacy, and algorithmic bias remain critical barriers to widespread adoption. The paper concludes by emphasizing the need for interdisciplinary collaboration, robust validation, and regulatory oversight to fully realize the potential of AI in precision medicine. By addressing these challenges, AI-powered precision medicine holds immense promise for delivering personalized, efficient, and equitable healthcare solutions.</p> |
| title | AI-Powered Precision Medicine: Transforming Healthcare through Intelligent Imaging and Surgical Ecosystem Innovation |
| topic | Artificial Intelligence Precision Medicine Medical Imaging Surgical Innovation Data Integration |
| url | https://doi.org/10.5281/zenodo.17018632 |