Application of artificial intelligence in the diagnosis, treatment, and recurrence prediction of peritoneal carcinomatosis
Peritoneal carcinomatosis (PC) is a type of secondary cancer which is not sensitive to conventional intravenous chemotherapy. Treatment strategies for PC are usually palliative rather than curative. Recently, artificial intelligence (AI) has been widely used in the medical field, making the early di...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-04-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024052800 |
| _version_ | 1797219305937436672 |
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| author | Gui-Xia Wei Yu-Wen Zhou Zhi-Ping Li Meng Qiu |
| author_facet | Gui-Xia Wei Yu-Wen Zhou Zhi-Ping Li Meng Qiu |
| author_sort | Gui-Xia Wei |
| collection | DOAJ |
| description | Peritoneal carcinomatosis (PC) is a type of secondary cancer which is not sensitive to conventional intravenous chemotherapy. Treatment strategies for PC are usually palliative rather than curative. Recently, artificial intelligence (AI) has been widely used in the medical field, making the early diagnosis, individualized treatment, and accurate prognostic evaluation of various cancers, including mediastinal malignancies, colorectal cancer, lung cancer more feasible. As a branch of computer science, AI specializes in image recognition, speech recognition, automatic large-scale data extraction and output. AI technologies have also made breakthrough progress in the field of peritoneal carcinomatosis (PC) based on its powerful learning capacity and efficient computational power. AI has been successfully applied in various approaches in PC diagnosis, including imaging, blood tests, proteomics, and pathological diagnosis. Due to the automatic extraction function of the convolutional neural network and the learning model based on machine learning algorithms, AI-assisted diagnosis types are associated with a higher accuracy rate compared to conventional diagnosis methods. In addition, AI is also used in the treatment of peritoneal cancer, including surgical resection, intraperitoneal chemotherapy, systemic chemotherapy, which significantly improves the survival of patients with PC. In particular, the recurrence prediction and emotion evaluation of PC patients are also combined with AI technology, further improving the quality of life of patients. Here we have comprehensively reviewed and summarized the latest developments in the application of AI in PC, helping oncologists to comprehensively diagnose PC and provide more precise treatment strategies for patients with PC. |
| first_indexed | 2024-04-24T12:31:33Z |
| format | Article |
| id | doaj.art-3a1b44785971420c8c09269fb38f6458 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-24T12:31:33Z |
| publishDate | 2024-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-3a1b44785971420c8c09269fb38f64582024-04-08T04:08:36ZengElsevierHeliyon2405-84402024-04-01107e29249Application of artificial intelligence in the diagnosis, treatment, and recurrence prediction of peritoneal carcinomatosisGui-Xia Wei0Yu-Wen Zhou1Zhi-Ping Li2Meng Qiu3Department of Abdominal Cancer, Cancer Center, West China Hospital of Sichuan University, Chengdu, ChinaDepartment of Colorectal Cancer Center, West China Hospital of Sichuan University, Chengdu, ChinaDepartment of Abdominal Cancer, Cancer Center, West China Hospital of Sichuan University, Chengdu, China; Corresponding author. Department of Abdominal Cancer, Cancer Center, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan Province, China.Department of Colorectal Cancer Center, West China Hospital of Sichuan University, Chengdu, China; Corresponding author. Department of Colorectal Cancer Center, West China Hospital of Sichuan University, 37 Guoxue Xiang Street, Chengdu, 610041, Sichuan Province, China.Peritoneal carcinomatosis (PC) is a type of secondary cancer which is not sensitive to conventional intravenous chemotherapy. Treatment strategies for PC are usually palliative rather than curative. Recently, artificial intelligence (AI) has been widely used in the medical field, making the early diagnosis, individualized treatment, and accurate prognostic evaluation of various cancers, including mediastinal malignancies, colorectal cancer, lung cancer more feasible. As a branch of computer science, AI specializes in image recognition, speech recognition, automatic large-scale data extraction and output. AI technologies have also made breakthrough progress in the field of peritoneal carcinomatosis (PC) based on its powerful learning capacity and efficient computational power. AI has been successfully applied in various approaches in PC diagnosis, including imaging, blood tests, proteomics, and pathological diagnosis. Due to the automatic extraction function of the convolutional neural network and the learning model based on machine learning algorithms, AI-assisted diagnosis types are associated with a higher accuracy rate compared to conventional diagnosis methods. In addition, AI is also used in the treatment of peritoneal cancer, including surgical resection, intraperitoneal chemotherapy, systemic chemotherapy, which significantly improves the survival of patients with PC. In particular, the recurrence prediction and emotion evaluation of PC patients are also combined with AI technology, further improving the quality of life of patients. Here we have comprehensively reviewed and summarized the latest developments in the application of AI in PC, helping oncologists to comprehensively diagnose PC and provide more precise treatment strategies for patients with PC.http://www.sciencedirect.com/science/article/pii/S2405844024052800Deep learningMachine learningArtificial intelligencePeritoneal carcinomatosis |
| spellingShingle | Gui-Xia Wei Yu-Wen Zhou Zhi-Ping Li Meng Qiu Application of artificial intelligence in the diagnosis, treatment, and recurrence prediction of peritoneal carcinomatosis Heliyon Deep learning Machine learning Artificial intelligence Peritoneal carcinomatosis |
| title | Application of artificial intelligence in the diagnosis, treatment, and recurrence prediction of peritoneal carcinomatosis |
| title_full | Application of artificial intelligence in the diagnosis, treatment, and recurrence prediction of peritoneal carcinomatosis |
| title_fullStr | Application of artificial intelligence in the diagnosis, treatment, and recurrence prediction of peritoneal carcinomatosis |
| title_full_unstemmed | Application of artificial intelligence in the diagnosis, treatment, and recurrence prediction of peritoneal carcinomatosis |
| title_short | Application of artificial intelligence in the diagnosis, treatment, and recurrence prediction of peritoneal carcinomatosis |
| title_sort | application of artificial intelligence in the diagnosis treatment and recurrence prediction of peritoneal carcinomatosis |
| topic | Deep learning Machine learning Artificial intelligence Peritoneal carcinomatosis |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024052800 |
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