Prognostic Models Using Machine Learning Algorithms and Treatment Outcomes of Occult Breast Cancer Patients.
Jingkun QuChaofan LiMengjie LiuYusheng WangZeyao FengJia LiWeiwei WangFei WuShuqun ZhangXixi ZhaoPublished in: Journal of clinical medicine (2023)
We analyzed the clinical features and prognostic factors of OBC patients; meanwhile, machine learning prognostic models with high precision and applicability were constructed to predict their overall survival. The treatment results in different molecular subtypes suggested that primary surgery might improve the survival of HR+/HER2- and HR-/HER2+ subtypes, however, only the HR-/HER2+ subtype could benefit from chemotherapy. The necessity of surgery and chemotherapy needs to be carefully considered for OBC patients with other subtypes.
Keyphrases
- prognostic factors
- machine learning
- minimally invasive
- coronary artery bypass
- end stage renal disease
- newly diagnosed
- locally advanced
- chronic kidney disease
- ejection fraction
- deep learning
- surgical site infection
- wastewater treatment
- artificial intelligence
- percutaneous coronary intervention
- acute coronary syndrome
- patient reported outcomes
- rectal cancer
- single molecule