News: Medical and Health
Malignant. Benign. If a picture tells a thousand words, these are the two jostling foremost in a patient’s mind when a radiologist scans their body for a better image of that suspicious lump or mass.But there is so much more a picture can tell us about cancer, particularly if we consider the possibilities of artificial intelligence.
Researchers from the University of Adelaide’s Australian Institute for Machine Learning (AIML) are developing a fully-automated medical image analysis program to detect breast tumours. The program uses a unique style to focus on the affected area.
The collaboration between AIML and LBT Innovations won the SA Science Excellence award for Research Collaboration for the development of that APAS technology.
We just had a piece on medical machine learning published in the Conversation.
AIML (formally ACVT) has been working with LBT Innovations, a South Australian medical device company, for more than 5 years on a new form of medical device to automate the reading of Agar plates.
A ten-week pivotal clinical trial at TriCore Reference Laboratories in New Mexico during July and August 2015 tested APAS against a panel of microbiologists. C
In another indication that the Machine Learning behind most Computer Vision Problems has more general applicability, we have just had a paper accepted which shows that the approach we developed for pedestrian detection achieves the world’s best performance in predicting protein-protein interactions.
LBT Innovations (ASX:LBT) has published the details of its extensive study into the accuracy of its Automated Plate Assessment System (APAS).
Lusia Guthrie was interviewed by Amanda Vanstone about our collaboration on the ABC’s Counterpoint program.