Electronic Design

Can tinyML Bring Machine Learning to the Masses?

Delivering smarter smarts to edge and free-standing devices, tinyML can be part of a broader AI/ML deployment. How tinyML differs from mainstream machine learning. How tinyML is being applied. What ...
ascopubs.org

Postprediction Inference for Clinical Characteristics Extracted With Machine Learning on Electronic Health Records

BatMan: Mitigating Batch Effects Via Stratification for Survival Outcome Prediction Real-world data (RWD) derived from electronic health records (EHRs) are often used to understand population-level ...
Electronic Design

Configurable 64-bit RISC-V IP Targets Machine Learning, Other Advanced Apps

Configurable high-bandwidth RISC-V cores with vector units can be made to directly address challenging applications like machine learning, AI, and other cutting-edge spaces. Semidynamics is a European ...
InsuranceNewsNet

Studies from University of Washington in the Area of Machine Learning Reported (Estimating heterogeneous impacts Of subsidised health insurance: A causal machine learning ...

By a News Reporter-Staff News Editor at Insurance Daily News-- Researchers detail new data in Machine Learning. According to news reporting out of Seattle, Washington, by NewsRx editors, research ...
Healio

Machine learning uses electronic health records to stratify food allergy risks in infants

Please provide your email address to receive an email when new articles are posted on . Random forest regression models had an area under the curve of 0.8 with 83% accuracy. The researchers called the ...
Neurology Advisor

Machine Learning Tool Predicts MS Relapse Risk After DMT Discontinuation

A machine learning–based tool accurately predicted risk for recurrent inflammatory activity after DMT discontinuation in MS, highlighting its potential to guide personalized treatment decisions.
Tech Xplore on MSN

Building better batteries with amorphous materials and machine learning

Lithium-ion batteries power most electronics, but they have limited energy density—they can store only a certain amount of energy per mass or volume of the battery.
BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
Aviation Week

Machine Learning-Trained Autonomy Tested By XQ-58 For Skyborg

An XQ-58 flies while controlled by machine-learning algorithms, as an F-15E observes. Credit: U.S. Air Force A Kratos XQ-58 Valkyrie has been flown for the first time with a certain tactical problem ...

IISc researchers use machine learning and amorphous materials to build high energy density batteries

The Indian Institute of Science (IISc) researchers, in a new study using a machine learning model and amorphous materials, ...