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Main Authors: Xinpei Deng, Yixuan Yan, Zekai Zhan, Jindong Xie, Hailin Tang, Yutian Zou, Jian Tu, Peng Liu
Format: Artículo Open Access
Published: Wiley 2024
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Online Access:https://onlinelibrary.wiley.com/doi/10.1002/imo2.19
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author Xinpei Deng
Yixuan Yan
Zekai Zhan
Jindong Xie
Hailin Tang
Yutian Zou
Jian Tu
Peng Liu
author_facet Xinpei Deng
Yixuan Yan
Zekai Zhan
Jindong Xie
Hailin Tang
Yutian Zou
Jian Tu
Peng Liu
Xinpei Deng
Yixuan Yan
Zekai Zhan
Jindong Xie
Hailin Tang
Yutian Zou
Jian Tu
Peng Liu
collection Wiley Open Access
contents A glimpse into the future: Integrating artificial intelligence for precision HER2‐positive breast cancer management Xinpei Deng Yixuan Yan Zekai Zhan Jindong Xie Hailin Tang Yutian Zou Jian Tu Peng Liu iMetaOmics AbstractBreast cancer (BC), specifically HER2‐positives subtype, has a poor prognosis. Nevertheless, the development of anti‐HER2 therapy yielded satisfactory outcomes. Therefore, evaluating patient HER2 status and ascertaining responsiveness to anti‐HER2 therapy is crucial. The advent of deep learning has propelled the artificial intelligence (AI) revolution, leading to an increased applicability of AI in predictive models. In the field of medicine, AI is an emerging modality that is gaining momentum for facilitating cancer diagnosis and treatment, particularly in the effective management of breast cancer. This study aims to provide a comprehensive review of current diagnostic and predictive models that utilize data obtained from histopathological slides, radiomics, and HER2 binding sites. Advancements and practical applications of these models were also evaluated. Additionally, we examined existing obstacles that AI encounters for anti‐HER2 therapy. We also proposed future directions for integrating AI in assessing and managing anti‐HER2 therapy. The findings of this study offer valuable insights into the evaluation of AI‐based anti‐HER2 therapy, emphasizing key concepts and obstacles that, if addressed, could facilitate the integration of AI‐assisted anti‐HER2 therapy. The integration of AI has the potential to enhance the precision and customization of screening and treatment protocols for HER2+ breast cancer. 10.1002/imo2.19 http://creativecommons.org/licenses/by/4.0/
doi_str_mv 10.1002/imo2.19
format Artículo Open Access
id wiley_oa_10_1002_imo2_19
institution Wiley Open Access
license_str_mv http://creativecommons.org/licenses/by/4.0/
publishDate 2024
publisher Wiley
record_format wiley_oa
spellingShingle A glimpse into the future: Integrating artificial intelligence for precision HER2‐positive breast cancer management
Xinpei Deng
Yixuan Yan
Zekai Zhan
Jindong Xie
Hailin Tang
Yutian Zou
Jian Tu
Peng Liu
iMetaOmics
A glimpse into the future: Integrating artificial intelligence for precision HER2‐positive breast cancer management Xinpei Deng Yixuan Yan Zekai Zhan Jindong Xie Hailin Tang Yutian Zou Jian Tu Peng Liu iMetaOmics AbstractBreast cancer (BC), specifically HER2‐positives subtype, has a poor prognosis. Nevertheless, the development of anti‐HER2 therapy yielded satisfactory outcomes. Therefore, evaluating patient HER2 status and ascertaining responsiveness to anti‐HER2 therapy is crucial. The advent of deep learning has propelled the artificial intelligence (AI) revolution, leading to an increased applicability of AI in predictive models. In the field of medicine, AI is an emerging modality that is gaining momentum for facilitating cancer diagnosis and treatment, particularly in the effective management of breast cancer. This study aims to provide a comprehensive review of current diagnostic and predictive models that utilize data obtained from histopathological slides, radiomics, and HER2 binding sites. Advancements and practical applications of these models were also evaluated. Additionally, we examined existing obstacles that AI encounters for anti‐HER2 therapy. We also proposed future directions for integrating AI in assessing and managing anti‐HER2 therapy. The findings of this study offer valuable insights into the evaluation of AI‐based anti‐HER2 therapy, emphasizing key concepts and obstacles that, if addressed, could facilitate the integration of AI‐assisted anti‐HER2 therapy. The integration of AI has the potential to enhance the precision and customization of screening and treatment protocols for HER2+ breast cancer. 10.1002/imo2.19 http://creativecommons.org/licenses/by/4.0/
title A glimpse into the future: Integrating artificial intelligence for precision HER2‐positive breast cancer management
topic iMetaOmics
url https://onlinelibrary.wiley.com/doi/10.1002/imo2.19