Active learning represents a transformative paradigm in machine learning, aimed at reducing the annotation burden by selectively querying the most informative data points. This approach leverages ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

Scientists from Peking University conducts a systematic review of studies on integrating machine learning into statistical methods in disease prediction models. Researchers from Peking University have ...

The AI revolution has transformed behavioral and cognitive research through unprecedented data volume, velocity, and variety (e.g., neural imaging, ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

Methods of K-12 teaching encompass diverse strategies and techniques utilized by educators to engage students across different subjects and grade levels. What are the 5 methods of teaching? From ...

The IAEA has launched an innovative, interactive e‑learning course on approaches and methods to help countries perform prospective radiological environmental impact assessment (REIA). Nuclear ...