AI heart disease prediction tools show promise but are not ready for clinical use: review

AI tools for predicting heart disease show potential but require further validation before clinical implementation, according to a systematic review.
pv magazine International

PV recycling challenges unlikely to be the same everywhere

A research team has used machine learning and spatial analysis to show that socioeconomic factors are most strongly ...
Finbold | Finance in Bold

Machine algorithm sets XRP price for August 1, 2026

XRP price is once again on a downward trend after last week’s brief stay above $1.1, and Finbold’s AI Agent finds that a reversal is not very likely in July. Namely, our machine learning algorithm ...
Invezz

Can ETH bulls defend crucial $1,500 support as selloff deepens? Check forecast

Second-order: if ETH is underperforming while the whole crypto market sells off, capital rotates toward the perceived “safer” large-cap. The article highlights ETH-specific weakness (loss of $1,700, ...
Morningstar

Machine Learning Can Forecast Which Stock Factors Will Outperform

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...
Frontiers

A support vector machine-based tool for rapid pediatric asthma exacerbation risk assessment: development and nursing application

Childhood asthma poses a significant threat to pediatric health, and traditional assessment methods are often inadequate in efficiency and accuracy. This study aims to develop a rapid assessment tool ...
Scientific Research Publishing

Cerqueira, V., Torgo, L. and Mozetič, I. (2020) Evaluating Time Series Forecasting Models: An Empirical Study on Performance Estimation Methods. Machine Learning, 109, 1997-2028.

ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...
Frontiers

Support vector machine-based classification of bulimia nervosa using diffusion tensor imaging

Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging (DTI) to ...
IEEE

Support Vector Machine-Integrated High-Definition MCPWM Technique for Improving Power Quality in Multilevel Inverters

Abstract: What if machine learning could predict inverter harmonics before prototyping? Conventional pulse width modulation (PWM) techniques in cascaded H-bridge (CHB) multilevel inverters (MLIs) ...