AIMC Topic: Chemotherapy, Adjuvant

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Machine learning with multiparametric magnetic resonance imaging of the breast for early prediction of response to neoadjuvant chemotherapy.

Breast (Edinburgh, Scotland)
In patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy (NAC), some patients achieve a complete pathologic response (pCR), some achieve a partial response, and some do not respond at all or even progress. Accurate predicti...

Robust identification of molecular phenotypes using semi-supervised learning.

BMC bioinformatics
BACKGROUND: Modern molecular profiling techniques are yielding vast amounts of data from patient samples that could be utilized with machine learning methods to provide important biological insights and improvements in patient outcomes. Unsupervised ...

Combining multimodal imaging and treatment features improves machine learning-based prognostic assessment in patients with glioblastoma multiforme.

Cancer medicine
BACKGROUND: For Glioblastoma (GBM), various prognostic nomograms have been proposed. This study aims to evaluate machine learning models to predict patients' overall survival (OS) and progression-free survival (PFS) on the basis of clinical, patholog...

Prediction of postoperative disease-free survival and brain metastasis for HER2-positive breast cancer patients treated with neoadjuvant chemotherapy plus trastuzumab using a machine learning algorithm.

Breast cancer research and treatment
PURPOSE: This study aimed to develop mathematical tools to predict the likelihood of recurrence after neoadjuvant chemotherapy (NAC) plus trastuzumab in patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer.

Immunomarker Support Vector Machine Classifier for Prediction of Gastric Cancer Survival and Adjuvant Chemotherapeutic Benefit.

Clinical cancer research : an official journal of the American Association for Cancer Research
Current tumor-node-metastasis (TNM) staging system cannot provide adequate information for prediction of prognosis and chemotherapeutic benefits. We constructed a classifier to predict prognosis and identify a subset of patients who can benefit from...

Prediction of Overall Survival and Novel Classification of Patients with Gastric Cancer Using the Survival Recurrent Network.

Annals of surgical oncology
BACKGROUND: Artificial neural networks (ANNs) have been applied to many prediction and classification problems, and could also be used to develop a prediction model of survival outcomes for cancer patients.

Optimal adjuvant endocrine treatment of ER+/HER2+ breast cancer patients by age at diagnosis: A population-based cohort study.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Prior randomised controlled trials on adjuvant hormonal therapy included HER2 patients; however, a differential effect of aromatase inhibitors (AIs) versus tamoxifen (TAM) may have been missed in ER+/HER2+ patients that comprise 7-15% of ...