Skip to content

Search for:

Topics
Our Bloggers
Our Substack
Follow Us!
- Bluesky
- Threads
- FaceBook
- Google News
- Twitter/X
Contribute/Contact

machine learning algorithms

Overview of prediction pipeline and models used across prediction tasks. We specified 3 modelling tasks for predicting premature death among people with inflammatory bowel disease (IBD). We then used 3 types of models, namely logistic regression, random forest, and Extreme Gradient Boosting (XGBoost); XGBoost was the only model used for task 3 as it enabled direct modelling of missing data (those without conditions would have missing data). See Related Content for accessible version. Note: CCS = chronic coronary syndrome, CHF = congestive heart failure, COPD = chronic obstructive pulmonary disease, ED = emergency department, HTN = hypertension, MI = myocardial infarction, RA = rheumatoid arthritis.

AI Finds Nearly Half of IBD Patients Die Prematurely

Categories Health, Technology

Researcher Jamie Lian leads ORNL’s contributions to a tool suite that uses machine learning for more effective cybersecurity analytics

Artificial intelligence tools secure tomorrow’s electric grid

Categories Earth, Energy & Environment, Technology

Bloggers

Cities of tomorrow: young Poles share vision for smarter, greener living
On the City of Fresno’s laudable waste-handling programs
Serving California’s PG&E, world’s first ultra-long duration hybrid green hydrogen energy storage microgrid moves forward
Truing the Sun
Hidden hunger in Europe: well fed yet undernourished
Where curiosity meets innovation: EU science fair in Belgium dazzles young minds
Spiralling weather and climate impacts documented in WMO report

© 2026 ScienceBlog.com | Follow our RSS / XML feed