The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...
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 ...
A recent study by Yale researchers demonstrated the potential of a machine learning approach to predict symptoms of post-traumatic stress disorder, or PTSD, for recent trauma survivors. Researchers ...
Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
This retrospective study included 643 patients who had undergone NSCLC resection. ML models (random forest, gradient boosting, extreme gradient boosting, and AdaBoost) and a random survival forest ...
The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...
Buildings produce a large share of New York's greenhouse gas emissions, but predicting future energy demand—essential for ...
A new artificial intelligence tool could aid in limiting or even prevent pandemics by identifying animal species that may harbor and spread viruses capable of infecting humans. The machine learning ...
The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...
Predictive Model of Acute Rectal Toxicity in Prostate Cancer Treated With Radiotherapy This retrospective study included 643 patients who had undergone NSCLC resection. ML models (random forest, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback