A model integrating deep learning with clinical and epidemiologic data may significantly improve lung cancer risk prediction based on LDCT screening.

From matchboxes to transformers, the entire arc of AI unfolds as a single elegant idea: that predicting patterns, across vision, games, language, and motion, is sufficient to produce genuine ...

Foundation model-powered dual-module system establishes a new performance benchmark for AI-driven peptide drug ...

Read more about Deep learning and AI unlock new era of solar energy forecasting and performance on Devdiscourse ...

Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...

Scientists develop spatiotemporal correlation-based deep learning framework for bias correction of atmospheric and oceanic variables ...

Researchers have developed an uncertainty quantification-based framework for predicting degradation trends in proton exchange ...

The multiple condition (MC)-retention model is an uncertainty-aware graph-based neural network that predicts liquid chromatography (LC) retention times across multiple column chem ...

Love Life Predictions for April 18, 2026: Choose the right time and setting for meetings. Move forward only after learning ...

In A Nutshell AI tools that track how the body’s molecular networks change over time may detect diseases like cancer, ...

Demis Hassabis (DeepMind CEO) and other AI leaders sees the next big AI gains—and the path to AGI—will come from targeted ...

Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).