Semiconductor Engineering

Overcoming Regression Debug Challenges With Machine Learning

Development of a modern semiconductor requires running many electronic design automation (EDA) tools many times over the course of the project. Every stage, from architectural exploration and design ...
Tech Xplore on MSN

AI-guided micromachining advances next-generation biocompatible titanium alloys

Researchers have developed a new machine-learning-assisted approach to optimize micro-electro-discharge machining (µ-EDM) of ...
The Lancet

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

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
ascopubs.org

Machine Learning Approach for Rapid, Accurate Point-of-Care Prediction of M-Spike Values in Multiple Myeloma

Random forest (RF) analysis identified the weighted value of each independent variable (N = 43) integrated into the ML algorithm. Pearson and Spearman coefficients indicated that the ML-predicted ...
Frontiers

Brain-Computer Interfaces (BCIs) for daily activities: Innovations in EEG signal analysis and machine learning approaches

Brain-Computer Interfaces (BCIs) are emerging as transformative tools that enable direct communication between the human ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...