Optimizing RNA design with AI and an Ising machine: Encoding matters

RNA has emerged as one of the most promising molecules in modern medicine, enabling advances from mRNA vaccines and gene ...

Researchers develop AI tool that finds the equations behind complex systems

Clarkson University researchers have developed an artificial intelligence tool that can uncover the mathematical equations ...
RMD Open

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still’s disease in fever of unknown origin: a retrospective …

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
C&EN

Synergism of Computational Simulation Technique and Machine Learning Algorithm for Prediction of Anticorrosion Properties of Some Antipyrine Derivatives

Africa Centre of Excellence in Future Energies and Electrochemical Systems - Federal University of Technology (ACEFUELS-FUTO), Owerri 460114, Imo State Nigeria Africa Centre of Excellence in Future ...
eLife

A novel machine learning algorithm selects proteome signature to specifically identify cancer exosomes

This important study introduces a novel AI method for the analysis of published data, with practical implications for early cancer diagnosis. The results are supported by compelling evidence.
IEEE

Comparative Performance Analysis of Machine Learning Algorithms for Arm and Shoulder Exercises Using Wrist-Worn Band

Abstract: The COVID-19 pandemic forcing many individuals to exercise at home without the supervision of a professional trainer, and maintaining proper posture during arm and shoulder exercises has ...
C&EN

Machine Learning Methods for Small Data Challenges in Molecular Science

Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States Department of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan ...
ascopubs.org

A Comparison of Logistic Regression Against Machine Learning Algorithms for Gastric Cancer Risk Prediction Within Real-World Clinical Data Streams

We trained models using logistic regression (LR) and four commonly used ML algorithms to predict NCGC from age-/sex-matched controls in two EHR systems: Stanford University and the University of ...