A machine learning model slightly outperforms a conventional regression model at predicting which children hospitalized for asthma will be readmitted within 180 days.
A new machine learning tool called T1GRS accurately predicts the genetic risk of developing Type 1 diabetes in both children ...
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 ...
Discover how machine learning asthma prediction can identify high-risk children early and support personalised care ...
Retrospective validation of a novel multimodal AI prognostic tool integrating digital pathology and clinical data against real world data and Oncotype DX in a Swiss breast cancer cohort. This is an ...
By analyzing CpG-based DNA methylation, the model achieved 87% accuracy when applied to 31 cases representing 17 different cancer types.
Machine learning can sound pretty complicated, right? Like something only super-smart tech people get. But honestly, it’s ...
A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...
In my latest Signal Spot, I had my Villanova students explore machine learning techniques to see if we could accurately ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results