on average, these human readers scrutinise 5,000 mammograms a year. 250 300 patients will be called back, and 30 a0 of those will require closer attention. and there is a chance that with that number you could miss cancers. within the rules that national screening council have given us, we are not allowed to use the ai automatically as part of the process as yet, so we are using the ai as an extra check at the end of our reading process. in 2016, a private company, keyron medical technologies, began training an ai model called nia using hundreds of thousands of medical scans. its job to identify breast cancer. until now, this ai has been intended as an assistive tool for use by two human radiologists. it has become the foundation of the technology being used in aberdeen. the health service is experiencing massive staff shortages. experimentation with al could relieve some of that pressure. the first clinical evaluation of its kind is being carried out here. 0rdinarily, two human radi
is on the left side. in screening, you want to pick up things that are small before they become big. programmes like this one identify breast cancer in roughly 6 in 1000 women. radiologists, known as readers, examine patient scans for signs of cancer. on average, these human readers scrutinise 5,000 mammograms a year. 250 300 patients will be called back, and 30 a0 of those will require closer attention. and there is a chance that with that number you could miss cancers. within the rules that the national screening council have given us, we are not allowed to use the ai automatically as part of the process as yet, so we are using the ai as an extra check at the end of our reading process. in 2016, a private company, keyron medical technologies, kheiron medical technologies, began training an ai model called nia using hundreds of thousands of medical scans.
there is a lesion in the left breast here, and of course this is something you would expect a human being. you can just tell there is something different in the pictures there, and if you click on this ai button, it circles an area to check. but the main area of most concern is this area circled here, where the cancer is on the left side. in screening, you want to pick up things that are small before they become big. programmes like this one identify breast cancer in roughly 6 in 1000 women. radiologists, known as readers, examine patient scans for signs of cancer. on average, these human readers scrutinise 5,000 mammograms a year. 250 300 patients will be called back, and 30 a0 of those will require closer attention. and there is a chance that with that number you could miss cancers. within the rules that national screening council have given us, we are not allowed to use the ai automatically as part of the process as yet, so we are using the ai as an extra check at the end of our rea
where there is part reading some of the normal mamograms, or where there is to improve our cancer detection as a safety net. this project is a collaboration between the nhs, the university of aberdeen and private companies microsoft providing cloud computing, and the ai model developed by keyron. the next step of the partnership is that we are taking our ai across the uk to over 30 nhs trusts, to over one million women to gain access to the ai screening. it has been a few weeks sincejune s biopsy, and i caught up with her via videocall. i wondered how she felt about an ai assisting in such sensitive work. your images are on screen and people are looking at them, whereas when it s an artificial intelligence, that feeling that somebody is looking in on has gone. the biopsy showed that i do have an early stage cancer, we certainly caught it at an earlier stage this time, but because i have had previous history with it,
here, where the cancer is on the left side. in screening, you want to pick up things that are small before they become big. programmes like this one identify breast cancer in roughly 6 in 1000 women. radiologists, known as readers, examine patient scans for signs of cancer. on average, these human readers scrutinise 5,000 mammograms a year. 250 300 patients will be called back, and 30 a0 of those will require closer attention. and there is a chance that with that number you could miss cancers. within the rules that national screening council have given us, we are not allowed to use the ai automatically as part of the process as yet, so we are using the ai as an extra check at the end of our reading process. in 2016, a private company, keyron medical technologies, began training an ai model called nia using hundreds of thousands of medical scans. itsjob to identify