News: Medical and Health

Medical Machine Learning for Preventing Blindness in Indigenous Communities

Johan

Congratulations to Dr Johan Verjans, Deputy Director of Medical Machine Learning at AIML, who has been named a Chief Investigator for the Medical Research Future Fund (MRFF) grant project looking at preventing Diabetic Retinopathy among Aboriginal Australians.

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AI to Help Transform Breast Cancer Screening

Gustavo Pic

Congratulations to AIML’s Professor Gustavo Carneiro who is part of the MRFF grant awarded to St Vincent’s Institute of Medical Research, allocating $2,260,100 in funding to research breast cancer screening technologies using AI!

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Australia keeps failing to see the opportunity of AI

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.

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Media Release: Tetris-like program could speed breast cancer detection

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. 

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First place!

Results for the REFUGE Retinal Fundus Glaucoma Challenge are in! First place in the Segmentation leaderboard and also in the Segmentation of Nuclei competition.

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Award for Excellence in Collaboration

Biomed

The collaboration between AIML and LBT Innovations won the SA Science Excellence award for Research Collaboration for the development of that APAS technology.

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AIML technology gets FDA approval

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.

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AIML medical imaging technology achieves 98% in FDA trials

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

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State of the art protein-protein interaction prediction

Sp

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.

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