Clinical approaches for integrating machine learning for patients with lymphoma: Current strategies and future perspectives.
Sign Up to like & getrecommendations! Published in 2023 at "British journal of haematology"
DOI: 10.1111/bjh.18861
Abstract: Machine learning (ML) approaches have been applied in the diagnosis and prediction of haematological malignancies. The consideration of ML algorithms to complement or replace current standard of care approaches requires investigation into the methods used… read more here.
Keywords: integrating machine; machine; machine learning; learning patients ... See more keywords
Integrating machine learning to construct aberrant alternative splicing event related classifiers to predict prognosis and immunotherapy response in patients with hepatocellular carcinoma
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Pharmacology"
DOI: 10.3389/fphar.2022.1019988
Abstract: Introduction: In hepatocellular carcinoma (HCC), alternative splicing (AS) is related to tumor invasion and progression. Methods: We used HCC data from a public database to identify AS subtypes by unsupervised clustering. Through feature analysis of… read more here.
Keywords: integrating machine; hepatocellular carcinoma; hcc; alternative splicing ... See more keywords