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 ...
Using routinely collected baseline data across 11 registries, prediction of remission showed limited discrimination and was best suited to ruling out remission. Performance was similar for a ...
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 ...
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