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 ...

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 ...

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...

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 ...

Gemini 3 combines multimodal understanding and coding to help you learn anything. Using Google AI Studio, see how Gemini 3 analyzes a complex research paper on materials science and deep learning to ...

Identification of a Suitable Subgroup for Radiation Dose Escalation in Definitive Concurrent Chemoradiation Therapy for Nonmetastatic Esophageal Squamous Cell Carcinoma The median follow-up for ...

Mamounas, MD, MPH, presented a multimodal–multitask deep learning algorithm designed to estimate late distant recurrence (DR) risk and help identify patients most likely to benefit from EET.