Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385264752> ?p ?o ?g. }
- W4385264752 abstract "Primary systemic therapy (PST) is the treatment of choice in patients with locally advanced breast cancer and is nowadays also often used in patients with early-stage breast cancer. Although imaging remains pivotal to assess response to PST accurately, the use of imaging to predict response to PST has the potential to not only better prognostication but also allow the de-escalation or omission of potentially toxic treatment with undesirable adverse effects, the accelerated implementation of new targeted therapies, and the mitigation of surgical delays in selected patients. In response to the limited ability of radiologists to predict response to PST via qualitative, subjective assessments of tumors on magnetic resonance imaging (MRI), artificial intelligence-enhanced MRI with classical machine learning, and in more recent times, deep learning, have been used with promising results to predict response, both before the start of PST and in the early stages of treatment. This review provides an overview of the current applications of artificial intelligence to MRI in assessing and predicting response to PST, and discusses the challenges and limitations of their clinical implementation." @default.
- W4385264752 created "2023-07-27" @default.
- W4385264752 creator A5005471188 @default.
- W4385264752 creator A5013701975 @default.
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- W4385264752 creator A5086157444 @default.
- W4385264752 date "2023-07-27" @default.
- W4385264752 modified "2023-09-30" @default.
- W4385264752 title "Artificial Intelligence-Enhanced Breast MRI" @default.
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- W4385264752 doi "https://doi.org/10.1097/rli.0000000000001010" @default.
- W4385264752 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37493391" @default.