New machine-learning models capture the rapid evolution of antimicrobial resistance

Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, ...

Neel Somani on How Privacy-Preserving Machine Learning Is Changing the Digital Landscape

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines.
clickondetroit.com

Allen Park postal worker death: What we know after man’s body found stuck in machine

ALLEN PARK, Mich. – A worker at a postal service facility in Allen Park was found dead after his body was stuck in a machine for several hours, officials said. Here’s what we know about this story so ...
Hosted on MSN

How to Compare Machine Learning Models Using Bootstrap Resampling in Scikit-Learn

Learn how to compare ML models using bootstrap resampling with a hands-on sklearn implementation. Social Security, Medicare are "going to be gone," Donald Trump warns Here's What To Do If You See A ...
SciELO

Machine learning for high-risk hospitalization prediction in outpatient individuals with diabetes at a tertiary hospital

Objective: To characterize, via a predictive model using real-world data, patients with diabetes with a heightened probability of hospitalization. Methods: At the Endocrinology Unit of a tertiary ...
TechRepublic

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers explore AI, ...
Frontiers

Comparison of machine learning methods for predicting ground-level ozone pollution in Beijing

With the accelerating pace of urbanization, air pollution has emerged as a critical global challenge, where ozone (O 3) concentration dynamics have become a pivotal indicator of atmospheric quality ...
IEEE

Addressing Data Imbalance in Crash Data: Evaluating Generative Adversarial Network’s Efficacy Against Conventional Methods

Abstract: In the realm of traffic safety analysis, the inherent imbalance in crash datasets, particularly in terms of injury severity, poses a significant challenge for machine learning-based ...