{"id":21494,"date":"2018-11-27T08:30:30","date_gmt":"2018-11-27T16:30:30","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=21494"},"modified":"2018-11-28T08:57:59","modified_gmt":"2018-11-28T16:57:59","slug":"healthcare-ai-results-vision-cancer","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2018\/11\/27\/healthcare-ai-results-vision-cancer\/","title":{"rendered":"Impressive Healthcare AI results for Vision Research & Cancer Treatment"},"content":{"rendered":"

This\u00a0insideBIGDATA special report series<\/a>\u00a0explores the intersection of AI and healthcare. In this entry, we cover some of the latest research and healthcare AI results for both vision research and cancer treatment. Discover how AI is impacting these areas of medicine.<\/em><\/p>\n

\"AI<\/a>

Download the full report.<\/a><\/p><\/div>\n

CSIRO Bionic Vision Research<\/strong><\/p>\n

Powered by the Dell EMC PowerEdge servers, CSIRO\u2019s large-scale scientific computing system provides capability for research in areas as diverse as virtual screening for therapeutic treatments, traffic and logistics optimization, modeling of new material structures and compositions, machine learning for image recognition, and pattern analysis.<\/p>\n

Dubbed \u201cBracewell,\u201d it is a turnkey system built on Dell EMC PowerEdge platform, with partner technology including NVIDIA GPUs for accelerated computation and Mellanox InfiniBand networking, which pieces all the compute nodes together in a low latency and high bandwidth solution faster than traditional Ethernet networking.<\/p>\n

One of the first research teams benefiting from the new processing power was Data61\u2019s Computer Vision group, led by Associate Professor Nick Barnes. His team developed the software for a bionic vision solution that aims to restore sight for those with profound vision loss, through new computer vision processing that uses large scale image datasets to optimize and learn more effective processing.<\/p>\n

A trial, held at the GP Superclinic at Midland Railway Workshops in Perth, was funded through an NHMRC grant and base funding from WA Health and CSIRO through the Australian Tele-health Research and Development Group. During the trial, general practitioners successfully screened 187 diabetic patients, taking high resolution images of their eyes, which were then analyzed by the technology for signs of diabetic retinopathy. The AI-enabled grading software, affectionately named Dr. Grader, was developed by researchers at CSIRO. By analyzing ophthalmologists\u2019 grading data, Dr. Grader was able to improve its ability to detect various signs of disease in patients.<\/p>\n

\"healthcare<\/a><\/p>\n

Importantly, as a basis for comparison, the images were also analyzed by an ophthalmologist, and the technology was found to be as effective as the specialist in detecting signs of diabetic retinopathy and grading its severity.<\/p>\n

Gustave Roussy Cancer Treatment<\/strong><\/p>\n

Key results: <\/strong><\/p>\n