Validity of the online PREDICT tool in older patients with breast cancer: a population-based study | British Journal of Cancer
Frontiers | A Risk Stratification Model for Predicting Overall Survival and Surgical Benefit in Triple-Negative Breast Cancer Patients With de novo Distant Metastasis
Evaluation of machine learning algorithms for the prognosis of breast cancer from the Surveillance, Epidemiology, and End Results database | PLOS ONE
5 Years, Still Alive – The Mental Breast
Accuracy of the online prognostication tools PREDICT and Adjuvant! for early-stage breast cancer patients younger than 50 years - ScienceDirect
Variability Among Breast Cancer Risk Classification Models When Applied at the Level of the Individual Woman | Journal of General Internal Medicine
Overall survival (OS) in patients with metastatic breast cancer... | Download Scientific Diagram
Prediction of Breast Cancer using Machine Learning Approaches
Development and internal-external validation of statistical and machine learning models for breast cancer prognostication: cohort study | The BMJ
PREDICT validity for prognosis of breast cancer patients with pathogenic BRCA1/2 variants | npj Breast Cancer
PDF) Development and validation of the PORTRET tool to predict recurrence, overall survival, and other-cause mortality in older patients with breast cancer in the Netherlands: a population-based study
A 23 gene–based molecular prognostic score precisely predicts overall survival of breast cancer patients - eBioMedicine
Development and validation of the PORTRET tool to predict recurrence, overall survival, and other-cause mortality in older patients with breast cancer in the Netherlands: a population-based study - The Lancet Healthy Longevity
Integrated multiomics analysis and machine learning refine molecular subtypes and prognosis for muscle-invasive urothelial cancer: Molecular Therapy - Nucleic Acids
Diagnosis and prognosis of breast cancer by high-performance serum metabolic fingerprints | PNAS
Validity of the prognostication tool PREDICT version 2.2 in Japanese breast cancer patients - Zaguirre - 2021 - Cancer Medicine - Wiley Online Library
Predicting factors for survival of breast cancer patients using machine learning techniques | BMC Medical Informatics and Decision Making | Full Text
Improving the performance of support-vector machine by selecting the best features by Gray Wolf algorithm to increase the accuracy of diagnosis of breast cancer | Journal of Big Data | Full Text
Correlation between Nottingham Prognostic Index and Adjuvant! Online prognostic tools in patients with early-stage breast cancer in Mid-Western Ireland. | Semantic Scholar
Interactive online consensus survival tool for esophageal squamous cell carcinoma prognosis analysis
Predicting better
PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients | Breast Cancer Research | Full Text
Circulating Tumor Cells, Disease Progression, and Survival in Metastatic Breast Cancer | NEJM
Frontiers | Prediction of Breast Cancer Recurrence Using a Deep Convolutional Neural Network Without Region-of-Interest Labeling
