Understanding the properties of different materials is an important step in material design. X-ray absorption spectroscopy ...

With heat waves among Europe's deadliest climate hazards, a team of scientists led by CMCC has developed a prediction system capable of providing helpful information four to seven weeks before summer, ...

Colonoscopy quality indicators for colorectal cancer precursors: Sessile serrated lesion and adenoma detection rates from a large clinical study of a blood-based test for CRC screening. This is an ...

Effect of KROS 101, a small molecule GITR ligand agonist, on T effector cells, T reg cells and intratumoral CD8 T cell cytotoxicity. Phase 1 study of DK210 (EGFR), a tumor-targeted IL2 x IL10 dual ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

Caltech scientists have developed an artificial intelligence (AI)–based method that dramatically speeds up calculations of the quantum interactions that take place in materials. In new work, the group ...

Explore how artificial intelligence and digital innovations are transforming sludge dewatering in wastewater systems, ...

When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...

Causal Machine Learning (CML) unites ML techniques with CI in order to take advantage of both approaches’ strengths. CML ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.