Clinical Interchangeability of PD-L1 Immunohistochemistry Assays in First-Line Non–Small Cell Lung Cancer Management With Cemiplimab Internal iliac and obturator lymph nodes are common sites of ...

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 ...

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

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 ...

The course emphasizes interpretable machine learning techniques and their applications in the financial services industry. Students will develop machine learning models, explain model predictions, and ...

RIT computer science professor Weijie Zhao has earned a National Science Foundation CAREER Award to defend machine learning ...

Researchers developed and externally validated a machine learning model to predict the 28-day mortality risk in ICU patients with sepsis complicated by acute respiratory failure. Using routinely ...

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, ...

Recent studies are using interpretable machine learning models alongside density functional theory (DFT) to predict reduction potentials of electrolyte solvents with high accuracy. By training on ...

The financial landscape of 2026 is defined by a paradox: machine learning systems are now more powerful and autonomous than ever, yet they operate under the strictest regulatory scrutiny in history.