Btw, my dentist used AI to identify potential problems in a radiograph. The result was pretty impressive. Have to get a filling tho.
No link or anything, very believable.
Honestly this is a pretty good use case for LLMs and I've seen them used very successfully to detect infection in samples for various neglected tropical diseases. This literally is what AI should be used for.
I had a housemate a couple of years ago who had a side job where she'd look through a load of these and confirm which were accurate. She didn't say it was AI though.
Can't pigeons do the same thing?
Neural networks are great for pattern recognition, unfortunately all the hype is in pattern generation and we end up with mammograms in anime style
Ductal carcinoma in situ (DCIS) is a type of preinvasive tumor that sometimes progresses to a highly deadly form of breast cancer. It accounts for about 25 percent of all breast cancer diagnoses.
Because it is difficult for clinicians to determine the type and stage of DCIS, patients with DCIS are often overtreated. To address this, an interdisciplinary team of researchers from MIT and ETH Zurich developed an AI model that can identify the different stages of DCIS from a cheap and easy-to-obtain breast tissue image. Their model shows that both the state and arrangement of cells in a tissue sample are important for determining the stage of DCIS.
https://news.mit.edu/2024/ai-model-identifies-certain-breast-tumor-stages-0722
https://youtube.com/shorts/xIMlJUwB1m8?si=zH6eF5xZ5Xoz_zsz
Detecting is not enough to be useful.
The test is 90% accurate, thats still pretty useful. Especially if you are simply putting people into a high risk group that needs to be more closely monitored.
A place for majestic STEMLORD peacocking, as well as memes about the realities of working in a lab.
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This is a science community. We use the Dawkins definition of meme.
