Nature

Survival Analysis Using Machine Learning Techniques

Recent progress in survival analysis has been driven by the integration of machine learning techniques with traditional statistical models, such as the Cox proportional hazards model. This synthesis ...
EurekAlert!

Prediction of age of onset of SCA3 and DRPLA by survival analysis using machine learning

Niigata, Japan – Using machine learning, the Department of Neurology at Niigata University has developed a model to predict the asymptomatic probability at each age from the current age and number of ...
ascopubs.org

Explainable Machine Learning Model to Predict Overall Survival in Patients Treated With Palliative Radiotherapy for Bone Metastases

Deep Learning-Based Dynamic Risk Prediction of Venous Thromboembolism for Patients With Ovarian Cancer in Real-World Settings From Electronic Health Records Data collected in the multicentric PRAIS ...
ascopubs.org

Machine Learning–Based Prediction of 1-Year Survival Using Subjective and Objective Parameters in Patients With Cancer

Palliative care is recommended for patients with cancer with a life expectancy of <12 months. Machine learning (ML) techniques can help in predicting survival outcomes among patients with cancer and ...
EurekAlert!

An interpretable machine learning model for predicting 5‐year survival in breast cancer based on integration of proteomics and clinical data

n this study, 773 untreated breast cancer patients from all over China were collected and followed up for at least 5 years. We obtained clinical data from 773 cases, RNA sequencing data from 752 cases ...
Frontiers

Soft Computing and Machine Learning Applications for Healthcare Systems

Soft Computing (SC) is an Artificial Intelligence (AI) approach that is more effective at solving real-life problems than traditional computing models. Soft Computing models are tolerant of partial ...