As the influenza season approaches, artificial intelligence (AI) tools and their developers are up for a test. Will AI tools analyzing symptom data, x-rays, and scans be able to distinguish an influenza patient from those with COVID-19?

An artificial intelligence algorithm 'ProteinSolver,' developed by computational biologists at the University of Toronto.is a neural network graph designed to create new proteins which mimics the Japanese puzzle "Sudoku." ProteinSolver computes novel amino-acid sequences for any protein fold known to be geometrically stable, but the end goal is to engineer novel protein structures with entirely new biological functions as new therapeutics.

Artificial Intelligence (AI) has the potential to speed up the time to bring a vaccine to market by accelerating the process of human trials.  

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.