Artificial intelligence in cancer pathology: Challenge to meet increasing demands of precision medicine
Clinical efforts on precision medicine are driving the need for accurate diagnostic, new prognostic and novel drug predictive assays to inform patient selection and stratification for disease treatment. Accumulating evidence suggests that a combination of cancer pathology and artificial intelligence...
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Published in | International journal of oncology Vol. 63; no. 3; p. 1 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Greece
Spandidos Publications
01.09.2023
Spandidos Publications UK Ltd |
Subjects | |
Online Access | Get full text |
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Abstract | Clinical efforts on precision medicine are driving the need for accurate diagnostic, new prognostic and novel drug predictive assays to inform patient selection and stratification for disease treatment. Accumulating evidence suggests that a combination of cancer pathology and artificial intelligence (AI) can meet this requirement. In the present review, the past, present and emerging integrations of AI into cancer pathology were comprehensively reviewed, which were divided into four main groups to highlight the roles of AI‑integrated cancer pathology in precision medicine. Furthermore, the unsolved problems and future challenges in AI‑integrated cancer pathology were also discussed. It was found that, although AI‑integrated cancer pathology could enable the amalgamation of complex morphological phenotypes with the multi‑omics datasets that drove precision medicine, synergies of cancer pathology with other medical tools could be more promising for the clinic when making an accurate and rapid decision in personalized treatments for patients. It was hypothesized by the authors that exploring the potential advantages of the multimodal integration of cancer pathology, imaging‑omics, protein‑omics and other‑omics, as well as clinical data to decide upon appropriate management and improve patient outcomes may be the most challenging issue of cancer precision medicine in the future. |
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AbstractList | Clinical efforts on precision medicine are driving the need for accurate diagnostic, new prognostic and novel drug predictive assays to inform patient selection and stratification for disease treatment. Accumulating evidence suggests that a combination of cancer pathology and artificial intelligence (AI) can meet this requirement. In the present review, the past, present and emerging integrations of AI into cancer pathology were comprehensively reviewed, which were divided into four main groups to highlight the roles of AI-integrated cancer pathology in precision medicine. Furthermore, the unsolved problems and future challenges in AI-integrated cancer pathology were also discussed. It was found that, although AI-integrated cancer pathology could enable the amalgamation of complex morphological phenotypes with the multi-omics datasets that drove precision medicine, synergies of cancer pathology with other medical tools could be more promising for the clinic when making an accurate and rapid decision in personalized treatments for patients. It was hypothesized by the authors that exploring the potential advantages of the multimodal integration of cancer pathology, imaging-omics, protein-omics and other-omics, as well as clinical data to decide upon appropriate management and improve patient outcomes may be the most challenging issue of cancer precision medicine in the future. |
ArticleNumber | 107 |
Audience | Academic |
Author | Jiang, Qingping Fu, Jianjiang Lai, Boan Peng, Juan Zhang, Qingxin Deng, Nan |
Author_xml | – sequence: 1 givenname: Boan surname: Lai fullname: Lai, Boan organization: Department of Pathology, Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510150, P.R. China – sequence: 2 givenname: Jianjiang surname: Fu fullname: Fu, Jianjiang organization: Department of Pathology, Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510150, P.R. China – sequence: 3 givenname: Qingxin surname: Zhang fullname: Zhang, Qingxin organization: Department of Pathology, Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510150, P.R. China – sequence: 4 givenname: Nan surname: Deng fullname: Deng, Nan organization: Department of Urology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510150, P.R. China – sequence: 5 givenname: Qingping surname: Jiang fullname: Jiang, Qingping organization: Department of Pathology, Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510150, P.R. China – sequence: 6 givenname: Juan surname: Peng fullname: Peng, Juan organization: Department of Pathology, Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510150, P.R. China |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37539741$$D View this record in MEDLINE/PubMed |
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Copyright | COPYRIGHT 2023 Spandidos Publications Copyright Spandidos Publications UK Ltd. 2023 |
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SubjectTerms | Artificial intelligence Brain cancer Cancer Care and treatment Medical diagnosis Neural networks Neurophysiology Pathology Patient education Precision medicine |
Title | Artificial intelligence in cancer pathology: Challenge to meet increasing demands of precision medicine |
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