A fast and accurate surrogate model screens over 10,000 possible metal-oxide supports for a platinum nanocatalyst to prevent sintering under high temperatures. Metal nanoparticles catalyze reactions ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

This new article publication from Acta Pharmaceutica Sinica B, discusses establishment of interpretable cytotoxicity prediction models using machine learning analysis of transcriptome features.

Influence of MRIs performed in a 6-week interval on the histopathological detection of prostate cancer with different PIRADS classifications: A real-world data analysis.

William Chiu (MSiA '13) works in the fast-paced world of finance, where algorithms often make decisions that impact millions of lives and even more dollars. Now he's helping MLDS students develop ...

This guest essay reflects the views of Nirali Somia, a graduate student at Cold Spring Harbor Laboratory. It is part of a series of essays from current researchers at the Cold Spring Harbor Laboratory ...

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...

A physics informed machine learning model predicts thermal conductivity from infrared images in milliseconds, enabling fast, ...

Spin density symmetry breaking in single-atom catalysts can significantly enhance the performance of hydrogen evolution reactions. Through interpretable machine learning and theoretical calculations, ...