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 ...
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 ...
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 ...
You have /5 articles left. Sign up for a free account or log in. Today on the Academic Minute, part of University of California, Irvine, Week: Jung In Park, assistant ...
Juntendo University researchers have trained a machine learning algorithm to use clinical information and physical function ...
BIOPREVENT’ AI tool predicts transplant-related immune conflict and mortality risk using biomarkers, helping doctors ...
A UCLA-led team has developed a machine-learning model that can predict with a high degree of accuracy the short-term survival of dialysis patients on Continuous Renal Replacement Therapy (CRRT). CRRT ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
At the University of California Irvine Sue & Bill Gross School of Nursing, faculty researchers are developing innovative new ways to harness artificial intelligence for improved patient care quality ...
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