The current research status on building prediction models for rectal cancer based on imaging data using artificial intelligence
［Abstract］ The advancement of artificial intelligence (AI) has opened new avenues for the clinical application of imaging data. Building prediction models based on imaging data can offer valuable insights for clinical diagnosis and treatment. The imaging data obtained from rectal cancer patients thr...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Colorectal & Anal Surgery
2023-10-01
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| Series: | 结直肠肛门外科 |
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| Online Access: | https://jcas.gxmuyfy.cn/cn/wqll/paper.html?id=195&cateName=2023%E5%B9%B4%20%E7%AC%AC29%E5%8D%B7%20%E7%AC%AC5%E6%9C%9F |
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| _version_ | 1849322668213403648 |
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| author | Zhang Tianshuai Peng Zhiying Jia Hang Wen Rongbo Zhou Leqi Shen Fu Yu Guanyu Zhang Wei |
| author_facet | Zhang Tianshuai Peng Zhiying Jia Hang Wen Rongbo Zhou Leqi Shen Fu Yu Guanyu Zhang Wei |
| author_sort | Zhang Tianshuai |
| collection | DOAJ |
| description | ［Abstract］ The advancement of artificial intelligence (AI) has opened new avenues for the clinical application of imaging data. Building prediction models based on imaging data can offer valuable insights for clinical diagnosis and treatment. The imaging data obtained from rectal cancer patients throughout the clinical diagnosis and treatment process represents a rich source of information. This article reviews the current research status on building prediction models for rectal cancer based on imaging data using AI methods, and it delves into the construction methods of prediction models, the clinical applications of these models, and the limitations of associated with their application. |
| format | Article |
| id | doaj-art-2682fffcfa67425a84dec24f66d56238 |
| institution | Kabale University |
| issn | 1674-0491 |
| language | zho |
| publishDate | 2023-10-01 |
| publisher | Editorial Office of Journal of Colorectal & Anal Surgery |
| record_format | Article |
| series | 结直肠肛门外科 |
| spelling | doaj-art-2682fffcfa67425a84dec24f66d562382025-08-20T03:49:17ZzhoEditorial Office of Journal of Colorectal & Anal Surgery结直肠肛门外科1674-04912023-10-0129552452910.19668/j.cnki.issn1674-0491.2023.05.022The current research status on building prediction models for rectal cancer based on imaging data using artificial intelligenceZhang Tianshuai0Peng Zhiying1Jia Hang2Wen Rongbo3Zhou Leqi4Shen Fu5Yu Guanyu6Zhang Wei7Department of Colorectal Surgery, Changhai Hospital, The First Affiliated Hospital of Naval Medical University, Shanghai 200433, ChinaDepartment of Colorectal Surgery, Changhai Hospital, The First Affiliated Hospital of Naval Medical University, Shanghai 200433, ChinaDepartment of Colorectal Surgery, Changhai Hospital, The First Affiliated Hospital of Naval Medical University, Shanghai 200433, ChinaDepartment of Colorectal Surgery, Changhai Hospital, The First Affiliated Hospital of Naval Medical University, Shanghai 200433, ChinaDepartment of Colorectal Surgery, Changhai Hospital, The First Affiliated Hospital of Naval Medical University, Shanghai 200433, ChinaDepartment of Radiology, Changhai Hospital, The First Affiliated Hospital of Naval Medical University, Shanghai 200433, ChinaDepartment of Colorectal Surgery, Changhai Hospital, The First Affiliated Hospital of Naval Medical University, Shanghai 200433, ChinaDepartment of Colorectal Surgery, Changhai Hospital, The First Affiliated Hospital of Naval Medical University, Shanghai 200433, China［Abstract］ The advancement of artificial intelligence (AI) has opened new avenues for the clinical application of imaging data. Building prediction models based on imaging data can offer valuable insights for clinical diagnosis and treatment. The imaging data obtained from rectal cancer patients throughout the clinical diagnosis and treatment process represents a rich source of information. This article reviews the current research status on building prediction models for rectal cancer based on imaging data using AI methods, and it delves into the construction methods of prediction models, the clinical applications of these models, and the limitations of associated with their application.https://jcas.gxmuyfy.cn/cn/wqll/paper.html?id=195&cateName=2023%E5%B9%B4%20%E7%AC%AC29%E5%8D%B7%20%E7%AC%AC5%E6%9C%9Frectal cancerartificial intelligenceimaging featuresprediction models |
| spellingShingle | Zhang Tianshuai Peng Zhiying Jia Hang Wen Rongbo Zhou Leqi Shen Fu Yu Guanyu Zhang Wei The current research status on building prediction models for rectal cancer based on imaging data using artificial intelligence 结直肠肛门外科 rectal cancer artificial intelligence imaging features prediction models |
| title | The current research status on building prediction models for rectal cancer based on imaging data using artificial intelligence |
| title_full | The current research status on building prediction models for rectal cancer based on imaging data using artificial intelligence |
| title_fullStr | The current research status on building prediction models for rectal cancer based on imaging data using artificial intelligence |
| title_full_unstemmed | The current research status on building prediction models for rectal cancer based on imaging data using artificial intelligence |
| title_short | The current research status on building prediction models for rectal cancer based on imaging data using artificial intelligence |
| title_sort | current research status on building prediction models for rectal cancer based on imaging data using artificial intelligence |
| topic | rectal cancer artificial intelligence imaging features prediction models |
| url | https://jcas.gxmuyfy.cn/cn/wqll/paper.html?id=195&cateName=2023%E5%B9%B4%20%E7%AC%AC29%E5%8D%B7%20%E7%AC%AC5%E6%9C%9F |
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