Comments on “Evaluation of the Accuracy of Mammography, Ultrasound and Magnetic Resonance Imaging in Suspect Breast Lesions”

An, Yongyu

doi:10.6061/clinics/2020/e2338

Cited by 3 publications

(1 citation statement)

References 10 publications

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“…Authors reply to Comments on ''Evaluation of the accuracy of mammography, ultrasound, and magnetic resonance imaging in suspect breast lesions'' performed by An (2020) (5). We mentioned in the Methods section that this was a retrospective study based on the review of electronic medical records from 2010 to 2018.…”

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confidence: 99%

Authors' Reply “Comments: Evaluation of the accuracy of mammography, ultrasound, and magnetic resonance imaging in suspect breast lesions”

Pereira¹,

Luz²,

Chagas³

et al. 2021

Clinics

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mentioning

confidence: 99%

Authors' Reply “Comments: Evaluation of the accuracy of mammography, ultrasound, and magnetic resonance imaging in suspect breast lesions”

Pereira¹,

Luz²,

Chagas³

et al. 2021

Clinics

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Clinicomics-guided distant metastasis prediction in breast cancer via artificial intelligence

Zhang

Cai

et al. 2023

BMC Cancer

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Background Breast cancer has become the most common malignant tumour worldwide. Distant metastasis is one of the leading causes of breast cancer-related death. To verify the performance of clinicomics-guided distant metastasis risk prediction for breast cancer via artificial intelligence and to investigate the accuracy of the created prediction models for metachronous distant metastasis, bone metastasis and visceral metastasis. Methods We retrospectively enrolled 6703 breast cancer patients from 2011 to 2016 in our hospital. The figures of magnetic resonance imaging scanning and ultrasound were collected, and the figures features of distant metastasis in breast cancer were detected. Clinicomics-guided nomogram was proven to be with significant better ability on distant metastasis prediction than the nomogram constructed by only clinical or radiographic data. Results Three clinicomics-guided prediction nomograms on distant metastasis, bone metastasis and visceral metastasis were created and validated. These models can potentially guide metachronous distant metastasis screening and lead to the implementation of individualized prophylactic therapy for breast cancer patients. Conclusion Our study is the first study to make cliniomics a reality. Such cliniomics strategy possesses the development potential in artificial intelligence medicine.

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Clinicomics-guided distant metastasis prediction in breast cancer via artificial intelligence

Zhang

Cai³

et al. 2022

Preprint

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Background: Breast cancer has become the most common malignant tumour worldwide. Distant metastasis is one of the leading causes of breast cancer-related death. To verify the performance of clinicomics-guided distant metastasis risk prediction for breast cancer via artificial intelligence and to investigate the accuracy of the created prediction models for metachronous distant metastasis, bone metastasis and visceral metastasis. Methods: We retrospectively enrolled 6703 breast cancer patients from 2011 to 2016 in our hospital. The figures of magnetic resonance imaging scanning and ultrasound were collected, and the figures features of distant metastasis in breast cancer were detected. Clinicomics-guided nomogram was proven to be with significant better ability on distant metastasis prediction than the nomogram constructed by only clinical or radiographic data. Results: Three clinicomics-guided prediction nomograms on distant metastasis, bone metastasis and visceral metastasis were created and validated. These models can potentially guide metachronous distant metastasis screening and lead to the implementation of individualized prophylactic therapy for breast cancer patients. Conclusion: Our study is the first study to make cliniomics a reality. Such cliniomics strategy possesses the development potential in artificial intelligence medicine.

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Comments on “Evaluation of the Accuracy of Mammography, Ultrasound and Magnetic Resonance Imaging in Suspect Breast Lesions”

Cited by 3 publications

References 10 publications

Authors' Reply “Comments: Evaluation of the accuracy of mammography, ultrasound, and magnetic resonance imaging in suspect breast lesions”

Authors' Reply “Comments: Evaluation of the accuracy of mammography, ultrasound, and magnetic resonance imaging in suspect breast lesions”

Clinicomics-guided distant metastasis prediction in breast cancer via artificial intelligence

Clinicomics-guided distant metastasis prediction in breast cancer via artificial intelligence

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