Ten simple rules for engaging with artificial intelligence in biomedicine

Artificial intelligence in the embryology laboratory: a review

“…AI is a general concept comprising diverse mathematical approaches with the capacity to make predictions based on complex pattern recognition by incorporating the processing power of computers (Malik et al, 2021). The selected algorithm(s) and the weight distribution attributed to its parameters define an AI model (Burkov 2019).…”

What do academics say about artificial intelligence ethics? An overview of the scholarship

“…The boundaries of AI ethics need to be taken into consideration, as well. The term overlaps with professional ethics in fields like medicine, healthcare, law, science, engineering, business, marketing, and finance, among others [1,16,28,44,53,63,91]. A related question is whether AI ethics should serve as an independent area of study and practice given its overlap with data ethics [40], digital ethics, machine ethics [92], and robot ethics [80], which are themselves contested terms.…”

Contributions on Computational Intelligence in the Medical Sector

“…To improve the sustainability of sizable sequencing data processing, CloudBurst makes parallel the short-read fourier transform. The CloudBurst concept was sorely assessed on a 25-core ensemble, and the results showed that it handled 7 million short-reads almost 30% faster than a single-core machine [9]. New CloudBurst-oriented biomedical research technologies created by the CloudBurst team include Contrail for reconstructing large genome and Slingshot for identifying single nucleotide polymorphisms (SNPs) from genome sequencing.…”