Proceedings of the National Academy of Sciences (PNAS)

Identifying variation in dinosaur footprints and classifying problematic specimens via unbiased unsupervised machine learning

Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
Psychology TodayOpinion

The Language Trap: How AI Writing Tools Are Standardizing Our Thoughts

As the use of generative AI becomes increasingly common, we must beware of an algorithmic colonization of language and ...
News Medical

Machine learning models can help diagnose ALS earlier from a blood sample

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic lateral sclerosis, or ALS, earlier from a blood sample, a study suggests. The ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
ahajournals.org

Abstract 4361575: Phenotyping Cardiogenic Shock Using Unsupervised Machine Learning: A Nationwide Cluster Analysis from National Inpatient Sample

Introduction: Cardiogenic shock (CS) is a heterogeneous clinical syndrome, with varied clinical outcomes driven by hemodynamic states, and initial presentation. However, unsupervised machine learning ...
TheServerSide

Sample Questions for AWS' Machine Learning Associate Certification

Community driven content discussing all aspects of software development from DevOps to design patterns. The AWS Machine Learning Associate certification validates your ability to configure, build, and ...
TheServerSide

Google Machine Learning Certification Sample Questions

Community driven content discussing all aspects of software development from DevOps to design patterns. The Google Cloud Professional Machine Learning Engineer certification validates your ability to ...
IEEE

A Review on Quantum Machine Learning in Applied Systems and Engineering

Abstract: Quantum Machine Learning (QML) has emerged as a promising frontier within artificial intelligence, offering enhanced data-driven modeling through quantum-augmented representation, ...
Scientific Research Publishing

Huang, A. A., & Huang, S. Y. (2023). Increasing Transparency in Machine Learning through Bootstrap Simulation and Shapely Additive Explanations. PLOS ONE, 18, e0281922.

ABSTRACT: Machine learning (ML) has revolutionized risk management by enabling organizations to make data-driven decisions with higher accuracy and speed. However, as machine learning models grow more ...
C&EN

Free-Energy Landscapes and Surface Dynamics in Methane Activation on Ni(511) via Machine Learning and Enhanced Sampling

Department of Chemical and Biomolecular Engineering, Tandon School of Engineering, New York University, 6 MetroTech Center, Brooklyn, New York 11201, United States Courant Institute of Mathematical ...
C&EN

Integrating Machine Learning-Based Pose Sampling with Established Scoring Functions for Virtual Screening

Department of Pharmaceutical Sciences, Division of Pharmaceutical Chemistry, Faculty of Life Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria Christian Doppler Laboratory ...