Deep neural networks could assess neurological problems
25 November, 2019Patients with neurological disorders, who may have impaired movement, could in future have their conditions assessed remotely rather than needing to meet with a doctor face to face.
ATCC launches portal of reference-quality genome sequences
25 October, 2019The ATCC Genome Portal is a publicly available database of reference-quality genome sequences matched to authenticated ATCC biological materials.
AI helps predict the effect of antidepressants
07 October, 2019Imaging the brain's activity in various states is important to get a more accurate picture of how depression manifests in a particular patient.
Thermo Scientific Avizo2D image analysis software
03 October, 2019 | Supplied by: Thermo Fisher ScientificThermo Scientific Avizo2D is an AI-powered automated imaging and analysis software designed to help materials and life science researchers acquire fast statistics from their electron microscopy (EM) images without extensive image processing expertise.
Bioinformatics platform helps manage biospecimen library
02 October, 2019 | Supplied by: AXT Pty LtdAs a central facility for storing blood and tissue samples, the Auckland Region Tissue Bank has a library that could hold the secrets to unlocking cures for chronic diseases and illnesses.
Deep learning deciphers what rats are saying
18 September, 2019 by Lisa Harvey, Managing Editor, MathWorks | Supplied by: MathWorks AustraliaFor many years, researchers knew that rodents' squeaks told a lot about how the animals are feeling.
Bitplane Imaris 9.3 image analysis software for life science
16 September, 2019 | Supplied by: SciTech Pty LtdBitplane's Imaris 9.3 is a software solution for correlative microscopy, enabling the possibility of opening multiple 2D, 3D or 4D datasets of differing spatial and temporal resolutions in the same scene.
How cloud computing is transforming the life sciences
13 September, 2019 by John Kaleski, Country Manager ANZ, Virtustream | Supplied by: EMC CorporationWhile striving to remain on the cutting edge of scientific discovery, researchers need more agile and powerful computing in order to drive towards a better future for everyone.
Creating a fully digitised pathology network
02 September, 2019 | Supplied by: Philips Components Pty LtdFaced with increasing demand for histopathology services in a vast but sparsely populated area in Australia, Sullivan Nicolaides Pathology was looking to increase its workflow efficiency.
Autoscribe Informatics Matrix Gemini LIMS
01 September, 2019 | Supplied by: Autoscribe Informatics Pty LtdAutoscribe Informatics' Matrix Gemini LIMS (laboratory information management system) is designed to be flexible enough for laboratories managing large volumes of data to strict standards.
AI can identify precancerous pancreatic cysts
12 August, 2019A laboratory test using artificial intelligence tools has the potential to more accurately sort out which people with pancreatic cysts will go on to develop pancreatic cancers.
AI better than humans at diagnosing skin lesions
20 June, 2019An international challenge compared the diagnostic skills of 511 physicians with 139 computer algorithms from 77 different machine learnings labs.
AI to improve rare disease diagnosis
14 June, 2019Two separate sets of European researchers have developed their own artificial intelligence methods to identify rare diseases, for which obtaining a definitive diagnosis can be difficult and time-consuming.
Aus researchers tackling antimicrobial resistance with AI
23 May, 2019A multi-institutional, multimillion-dollar project to understand how antimicrobial-resistant bacteria spread, and to develop new ways to combat it, has won a $1 million grant.
Sartorius Stedim Data Analytics SIMCA 16 software for Multivariate Data Analytics
16 May, 2019 | Supplied by: Sartorius Australia Pty LtdSartorius Stedim Data Analytics has announced SIMCA 16 software for multivariate data analytics. The updated SIMCA focuses on delivering a complete data analysis experience, from data organisation through to data-driven decision-making, supported by multivariate models for single and multiblock analysis.
