Building a machine learning-assisted echocardiography prediction tool for children at risk for cancer therapy-related cardiomyopathy

Abstract Background Despite routine echocardiographic surveillance for childhood cancer survivors, the ability to predict cardiomyopathy risk in individual patients is limited. We explored the feasibility and optimal processes for machine learning-enhanced cardiomyopathy prediction in survivors usin...

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主要な著者:	Lindsay A. Edwards, Christina Yang, Surbhi Sharma, Zih-Hua Chen, Lahari Gorantla, Sanika A. Joshi, Nicolas J. Longhi, Nahom Worku, Jamie S. Yang, Brandy Martinez Di Pietro, Saro Armenian, Aarti Bhat, William Border, Sujatha Buddhe, Nancy Blythe, Kayla Stratton, Kasey J. Leger, Wendy M. Leisenring, Lillian R. Meacham, Paul C. Nathan, Shanti Narasimhan, Ritu Sachdeva, Karim Sadak, Eric J. Chow, Patrick M. Boyle
フォーマット:	Artigo
言語:	Inglês
出版事項:	BMC 2024-10-01
シリーズ:	Cardio-Oncology
主題:	Machine learning Cardiomyopathy Cancer survivorship Echocardiography
オンライン･アクセス:	https://doi.org/10.1186/s40959-024-00268-4
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