Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
UC San Diego Today

A New Method to Steer AI Output Uncovers Vulnerabilities and Potential Improvements

A team of researchers has found a way to steer the output of large language models by manipulating specific concepts inside these models. The new method could lead to more reliable, more efficient, ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
IEEE

Hybrid Models for Classifying Liver Cirrhosis with SVM and Xgboost Algorithms

Abstract: Detecting and controlling cirrhosis that destroy liver tissue is major issue in liver part. More complex machine learning may better predict this complex disease. In this paper, a novel ...
IEEE

COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization

Abstract: Post-training quantization (PTQ) has emerged as a practical approach to compress large neural networks, making them highly efficient for deployment. However, effectively reducing these ...