EurekAlert!

Using multimodal deep learning to detect malicious traffic with noisy labels

The success of a deep learning-based network intrusion detection systems (NIDS) relies on large-scale, labeled, realistic traffic. However, automated labeling of realistic traffic, such as by sand-box ...
News Medical

COMET model enhances disease prediction with deep learning

COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...
ascopubs.org

Deep-learning model for real-time prediction of recurrence in early-stage non-small cell lung cancer: A multi-modal approach.

Implications of EGFR expression in MAPK dependency and adaptive immunity status of EGFR-mutated lung adenocarcinoma. Baseline RADAR score and optimal threshold of predicting relapse within one year ...
eSchool News

Where AI and multimodal learning will go in 2025

Reflecting on the developments of 2024, this year has been transformative for the entire educational landscape. We’ve witnessed how the thoughtful integration of artificial intelligence can elevate ...

ECOG-ACRIN and Caris Life Sciences unveil first findings from a multi-year collaboration to advance AI-powered multimodal tools for breast cancer recurrence risk stratification

Today at the San Antonio Breast Cancer Symposium (SABCS), researchers presented the initial findings from a major multi-year collaboration between the ECOG-ACRIN Cancer Research Group (ECOG-ACRIN) and ...