eLife

Separating selection from mutation in antibody language models

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
The American Journal of Managed Care

Model Aids IPF Diagnosis and Treatment in TCM

A hybrid model combining LM, GA, and BP neural networks improves TCM's diagnostic accuracy for IPF, achieving 81.22% ...
Frontiers

Enhanced SQL injection detection using chi-square feature selection and machine learning classifiers

Computational and Communication Science and Engineering (CoCSE), The Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha, Tanzania In the face of increasing cyberattacks, ...
Digital Trends

Perplexity AI turns into tutor with new language learning feature

What’s happened? Perplexity AI just dropped a new language learning feature built right into its platform. In a post shared on social media, the company announced a tool that helps users learn by ...
IEEE

Feature Selection for Battery Lifetime Prediction using Explainable Machine Learning

Abstract: Accurate battery lifetime estimation is crucial for health management and system safety. Data-driven research yields extensive feature sets, yet optimal feature selection is often impeded by ...
Frontiers

Spectroscopic detection of cotton Verticillium wilt by spectral feature selection and machine learning methods

Introduction: Verticillium wilt is a severe soil-borne disease that affects cotton growth and yield. Traditional monitoring methods, which rely on manual investigation, are inefficient and impractical ...
IEEE

Variability-Aware Machine Learning Model Selection: Feature Modeling, Instantiation, and Experimental Case Study

Abstract: The emergence of machine learning (ML) has led to a transformative shift in software techniques and guidelines for building software applications that support data analysis process ...