Opinion
Tech XploreOpinion

Generative AI may cut costs in machine-learning systems, but it increases risks of cyberattacks and data leaks

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...
Tech Xplore

Teaching AI models to say 'I'm not sure' in cases of calibration errors

Confidence is persuasive. In artificial intelligence systems, it is often misleading. Today's most capable reasoning models ...

In bone imaging, machine learning accelerates research progress and uncovers hidden patterns

In a future perhaps not too far away, artificial intelligence and its subfield of machine learning (ML) tools and models, ...
Market.us Scoop

Anomaly Detection Market Towards US$ 33.32 Billion by 2035

Anomaly Detection Market is predicted to register growth from USD 5.61 bn in 2025 to about USD 33.32 bn by 2035, recording a ...
Scientific Research Publishing

Dietterich, T.G. (2000) Ensemble Methods in Machine Learning. In: Kittler, J. and Roli, F., Eds., International Workshop on Multiple Classifier Systems, Springer, 1-15.

ABSTRACT: This paper proposes a hybrid machine learning framework for early diabetes prediction tailored to Sierra Leone, where locally representative datasets are scarce. The framework integrates ...
The Lancet

When to and when not to use machine learning in risk prediction models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...
chromatographyonline

A Novel Machine Learning Method for Predicting Retention Time of Small Molecule Pharmaceutical Compounds Across Reversed-phase HPLC Columns

Traditional QSRR models are limited to single-column predictions, hindering adaptability across diverse LC setups in pharmaceutical settings. The new ML-based approach predicts retention times using ...
openaccessgovernment

Leveraging machine learning and robust small area estimation methods for stand-level forest inventory

This special report introduces small area estimation (SAE) as a modern approach for producing reliable, stand-level forest inventory information Small area estimation (SAE) is a set of statistical ...
IPWatchdog

SCOTUS Scraps Recentive’s Petition Seeking Clarity on Eligibility for Machine Learning Claims

“On appeal, the CAFC agreed that ‘the patents are directed to the abstract idea of using a generic machine learning technique in a particular environment, with no inventive concept’.” The U.S. Supreme ...
C&EN

Prioritizing Data Quality in Machine Learning for Thermophysical Property Prediction: A Case Study on Normal Boiling Points of Organic Compounds

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. No ...
Scientific Research Publishing

Estimating Heterogeneous Treatment Effects of Early Childhood Interventions on Fifth-Grade Math Achievement: A Machine Learning-Augmented Causal Analysis of ECLS-K:2011 ()

School of Economics, The University of Nottingham-Ningbo, Ningbo, China. The study focuses on identifying and distinguishing whether there are differences between those students receiving special ...