Artificial Intelligence (AI) has the potential to speed up the time to bring a vaccine to market by accelerating the process of human trials.
Automated biosurveillance is promising in terms of both improving public health response to natural disease outbreaks and minimizing potential casualties from the utilization of biological weapons.
800+ attendees and 200+ industry leading speakers: global leaders in AI, data, drug discovery and development, genomics, and quantum computing from pharma, VC, health systems, biotech, academia, research institutes, startups and bleeding edge solution providers.
Software helps sharpen images taken under the microscope to allow researchers to see cells clearly.
Using artificial intelligence, scientists created a tool to detect banana diseases and pests with a 90 percent success rate.
According to a study conducted at Saint Louis University, artificial intelligence (AI) has the ability to analyze routinely captured data to monitor handwashing compliance within hospitals and provide feedback to individual healthcare workers.
As microbial geneticists start to utilize machine learning to analyze their data, microbiologist Nick Loman of the University of Birmingham cautions that scientists have plunged ahead with using artificial intelligence without fully understanding its benefits and limitations.
A consortium of14 organizations will develop an Australia-wide antimicrobial resistance knowledge engine to anticipate outbreaks and inform interventions.
HRMAn uses deep neural networks to analyse complex patterns in images of pathogen and human ('host') cell interactions, pulling out the same detailed characteristics that scientists do by-hand.
A trial underway at Western Australia's Murdoch University is tipped to save time and money by using artificial intelligence to digitally identify plants, vertebrates and insects suspected to pose a biosecurity threat.