A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

To create their contactless approach, the researchers created a machine learning algorithm capable of analyzing aspects of ...

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 ...

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

For the first time, researchers have used machine learning—a type of artificial intelligence (AI)—to identify the most ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

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 ...

Pancreatic cancer mortality trends (2018-2023): Exposing racial inequities in Michigan's cancer burden. AUC for the PurIST baseline, the top 2 unimodal models, and the best fusion model for each ...

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 ...