Description
Predict patient mortality to provide appropriate support
Linked Case Studies
Case Study
Imperial College London
Imperial College Researchers diagnose ovarian cancer patients with survival rates under 2 years
Case Study
KenSci
KenSci improves on prediction models of mortality risk six months to one year out through deep machine learning leading to better palliative care
Case Study
Stanford University
Stanford University Medical uses machine learning to improve palliative care by predicting end-of-life within the next year with 90% accuracy
Case Study
Google
Google Health improves predictions of hospital patient medical outcomes by using deep neural networks trained on 46 billion data points
Case Study
Stanford University
Stanford University researchers plan to improve palliative care by predicting mortality of patient with deep learning
Case Study
Florida State University
Researchers at Florida State University predict one-year mortality rate in ICU patients suffering from a heart disease
Case Study
PLA General Hospital
PLA General Hospital in Beijing is using an algorithm for predicting if patients will wake up from a coma
Case Study
The Francis Crick Institute
Scientists at the Francis Crick Institute outperform medical models at predicting risk of death in patients with heart disease using machine learning