Autoscribe Release Hazardous Waste Tracking Software
News May 21, 2014
This Windows-based system features a dual web/Windows user interface and allows the registration of hazardous waste items, progress/status checking, chain of custody management and reporting, lookup of EWC lists and consignment of hazardous waste. Details of carrier, consignee and users, with their associated authority, are all stored within the system.
The system accommodates EU, Environment Agency, GLP, GMP and ISO9000 requirements by automatically recording who performed essential functions related to a sample and when they occurred. All actions are fully audited and retained within the database for enhanced traceability and accountability.
Matrix Hazardous Waste Tracker is fully configurable via Autoscribe’s unique OneTime™ configuration tools for use over the LAN, WAN or Web. This allows the system to be designed to reflect local needs e.g. work flow design, screen design, terminology etc. Work/sample registration provides a “browser” for selecting waste hazard codes which automatically assigns a series of tests to the sample. Automatic label generation with barcodes is supported.
The system is supplied with a standard suite of functional reports. Further reports can be configured to include worksheets, work pending, sample/work status, waste status on-site and waste status consigned off-site for specified date ranges and full audit trail depending on local needs.
Algorithm Speeds Up Medical Image Analysis 1000 TimesNews
Medical image registration is a common technique that involves overlaying two images, such as magnetic resonance imaging (MRI) scans, to compare and analyze anatomical differences in great detail. Researchers have described a machine-learning algorithm that can register brain scans and other 3-D images more than 1,000 times more quickly using novel learning techniques.
Antarctic Worm and Machine Learning Help Identify Cerebral Palsy EarlierNews
A research team has released a study in the peer-reviewed journal BMC Bioinformatics showing that DNA methylation patterns in circulating blood cells can be used to help identify spastic cerebral palsy (CP) patients. The technique which makes use of machine learning, data science and even analysis of Antarctic worms, raises hopes for earlier targeted CP therapies.
Towards Personalized Medicine: One Type of Data is Not EnoughNews
To understand the biology of diseased organs researchers use different types of molecular data. One of the biggest computational challenges at the moment is integrating these multiple data types. A new computational method jointly analyses different types of molecular data and disentangles the sources of disease variability to guide personalized treatment.READ MORE