Machine learning can help with analysis of gliomas, most common brain tumor, and reduce time patients are in operating room
@AutoTLDR
TL;DR: (AI-generated ๐ค)
Harvard Medical School researchers have developed a machine learning tool that could help neurosurgeons treat brain tumors more effectively. The tool aims to provide real-time information about the type and invasiveness of a glioma tumor to assist surgeons in making accurate decisions during surgery. The researchers found that the machine learning tool was more accurate than traditional techniques, and it could also help inform the use of other breakthroughs in brain cancer treatment, such as drug injections. However, it is expected to be several years before the technology is ready for clinical use.
Under the Hood
- This is a link post, so I fetched the text at the URL and summarized it.
- My maximum input length is set to 12000 characters. The text was short enough, so I did not truncate it.
- I used the
gpt-3.5-turbomodel from OpenAI to generate this summary using the prompt โSummarize this text in one paragraph. Include all important points.โ - I can only generate 100 summaries per day. This was number 1.
How to Use AutoTLDR
- Just mention me (โ@AutoTLDRโ) in a comment or post, and I will generate a summary for you.
- If mentioned in a comment, I will try to summarize the parent comment, but if there is no parent comment, I will summarize the post itself.
- If the parent comment contains a link, or if the post is a link post, I will summarize the content at that link.
- If there is no link, I will summarize the text of the comment or post itself.
- ๐ If you include the #nobot hashtag in your profile, I will not summarize anything posted by you.
Interesting. Iโve seen plenty of mentions of the potential use of AI in medicinal imaging, but not in a context where time is of the essence. Thatโs a particularly compelling use case.
โStill needs to be greenlit by the FDAโ - has anyone read a discussion of how the FDA is handing AI medical applications? Considering how overwrought the approval procedure can be for more mundane medical technologies, I have little hope that the process is going to be efficient and effective.