The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

Deep neural networks have rapidly advanced, with many models demonstrating outstanding performance. However, robustness is crucial for ensuring the safety and stability of artificial intelligence, ...

This important study presents a new method for longitudinally tracking cells in two-photon imaging data that addresses the specific challenges of imaging neurons in the developing cortex. It provides ...

Squid Game was once a sharp critique of capitalist excess. Now that Season 3 has arrived, the show feels like just another victim of it.

Numerical simulations and experimental tests demonstrate that the hybrid multi-population genetic algorithm, integrated with the improved 2-opt and 1-opt local search strategies, exhibits superior ...

Deep learning algorithm used to pinpoint potential disease-causing variants in non-coding regions of the human genome The methods help identify 'footprints' that indicate binding sites and reveal ...

Many 23andMe customers signed up to the genetic testing service in hopes of learning fun or interesting information about their past. But consumer advocates are now urging those users to request ...

A hybrid intelligent algorithm integrating Q-learning is innovatively designed, using a genetic algorithm as the main framework while embedding a quay crane allocation module and dynamically selecting ...

This paper proposes a Random Forest grid fault prediction model based on Genetic Algorithm optimization (GA-RF) to classify the grid fault types, which improves the distribution network fault ...

During the process of determining the arrival directions and beam conformation at the antennas, different types of algorithms can be used, namely deterministic algorithms and heuristics. Genetic ...

Genetic algorithms evaluate potential solutions by evolving them over many generations and keeping the ones which work best each time.