Large AI models can speed catalyst discovery by predicting performance before synthesis

Artificial intelligence (AI) is transforming the way scientists discover and design new materials. In a specially invited review published in Angewandte Chemie International Edition, Tohoku University ...
News-Medical.Net

Machine learning model may provide an earning warning of preeclampsia in late gestation

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

Machine learning can predict preeclampsia by week 34 of pregnancy

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...
IEEE

Machine-Learning-Based Urban Path Loss Prediction at 900 MHz: Principal Component Analysis, Clustering, Feature Importance and Regression

Abstract: In this work, the possibility of applying machine learning (ML) techniques to analyze and predict radio wave propagation losses in urban environments is explored. Thus, from a measurement ...
The New York Times

Betting on Prediction Markets Is Their Job. They Make Millions.

Welcome to the era of the Polymarket sharp. Joel Holsinger made hundreds of dollars on Kalshi after correctly guessing which turkey President Trump would pardon last year.Credit...Oliver Farshi for ...
IEEE

Explainable E-Commerce Transaction Prediction Using LightGBM and Permutation Importance

Abstract: This study develops an explainable machine learning framework for predicting e-commerce transaction volumes by integrating Light Gradient Boosting Machine (LightGBM), Permutation Feature ...
csis.org

Avoiding Catastrophe: The Importance of Privacy when Leveraging AI and Machine Learning for Disaster Management

In developing countries, the impact of significant events such as earthquakes, extreme weather, terrorist attacks, cyber incidents, or health emergencies can be more pronounced given the lack of ...
Frontiers

Local-NPDR: a novel variable importance method for explainable machine learning and false discovery diagnosis for ocean worlds biosignatures

Explainable machine learning (ML) is important for biosignature prediction on future astrobiology missions to minimize the risk of false positives due to geochemical biotic mimicry and false negatives ...