Quanta Magazine

Fed on Reams of Cell Data, AI Maps New Neighborhoods in the Brain

Machine learning is helping neuroscientists organize vast quantities of cells’ genetic data in the latest neurobiological cartography effort.
IEEE

Machine Learning Algorithms for Predicting Drug Efficacy and Adverse Effects Based on Individual Genetic Profiles

Abstract: ADRs, or adverse drug reactions, are a chronic problem in drug development and patient safety, frequently resulting in expensive clinical failures and serious health outcomes. Conventional ...
Frontiers

A Hybrid Metaheuristic Algorithm with Machine Learning for Detecting Denial-of-Service Attacks in Wireless Sensor Networks

The final, formatted version of the article will be published soon. Abstract. Denial-of-service (DoS) attacks pose a major threat to various kinds of computer networks. There are several kinds of ...
AZoRobotics

AI in Vaccine Development: How Machine Learning is Speeding Up Discovery

What if vaccine development didn’t have to take a decade? This piece looks at how AI is helping scientists ask better ...
Market.us Scoop

AI Enabled Predictive Toxicology Market Forecast to Surpass USD 4.9 Billion by 2033

Global AI In Predictive Toxicology Market size is expected to be worth around USD 4,964.3 Million by 2033 ...

Deep-learning algorithms enhance mutation detection in cancer and RNA sequencing

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning ...
IEEE

Research on Optimization Strategy Based on Fusion of Genetic Algorithm and Machine Learning Model

Abstract: This research focuses on the solution of optimization problem, through the construction of INS-GA model, the genetic algorithm is used to optimize the data combination, and the elite ...
GitHub

Machine Learning Classification of Pathogenic vs. Benign Coding Genetic Variants

This capstone project develops a machine learning pipeline to classify coding genetic variants as pathogenic versus benign using pretrained protein language model embeddings (ESM2). The work supports ...