The studies we reviewed show that the use of AI has improved the radiologists’ performances, treatment response, diagnostic accuracy, and decision-making in handling complex cases.
Hardly a game changer of the magnitude you think of. Moreover, CV is not generative. Pattern matching on X-rays has been common for a while, and has little to do with the current heavily marketed landscape of LLMs for everything.
This is one article. Are you actually interested in learning about the benefit of AI in cancer research? I could post a dozen articles, but would it make a difference to you? Also keep in mind it’s only going to get better as the models improve. I suspect your position is more ideological rather than rational.
And I suspect your position comes from not doing any due diligence on the matter.
Funny that you call mine “ideological” though, since you are the one making claims without any substance, e.g. “it’s only going to get better”. How could you even know? Not even researchers at the very edge do. There have been concerns about the future availability and quality of data. Plenty of researchers have come forward pointing that poisoning a LLM is exceedingly easy. Really, how do you know that “it’s going to get better”? Explain that to me. What do you know that everybody else doesn’t?
How do you even know that AI, as we know it, it’s going to be revolutionary in the near future? Most people only know of technology successes because of survivorship bias, but I’ve been through several revolutions that faded out. How is this one different? And why would you think you’re right, when not even expert researchers are sure?
“AI-powered platforms are now accelerating molecular subtyping, refining risk stratification, and supporting individualized therapeutic recommendations by jointly modeling imaging, tissue architecture, and molecular landscapes. Moreover, emerging virtual cell and mechanistic foundation frameworks introduce a new computational paradigm for simulating cellular responses and drug-tumor interactions, offering predictive insights for treatment design and drug discovery.”
Again, CV is not new. Computational biological simulation isn’t new either. More computational power and better algorithms have been a source of significant progress in healthcare for many decades now. If we go back twenty years, protein folding simulation was all the rage, but of course most people outside CompSci hadn’t heard of it.
I call the current AI “hype” because all these advancements have been going on for a while, but most people are catching up only now because they got hooked on marketing material they see on the news.
Anyway, I’m going to paste my message here once again.
Funny that you call mine “ideological” though, since you are the one making claims without any substance, e.g. “it’s only going to get better”. How could you even know? Not even researchers at the very edge do. There have been concerns about the future availability and quality of data. Plenty of researchers have come forward pointing that poisoning a LLM is exceedingly easy. Really, how do you know that “it’s going to get better”? Explain that to me. What do you know that everybody else doesn’t?
How do you even know that AI, as we know it, it’s going to be revolutionary in the near future? Most people only know of technology successes because of survivorship bias, but I’ve been through several revolutions that faded out. How is this one different? And why would you think you’re right, when not even expert researchers are sure?
Now, are you an AI researcher? What do you know about any of this, exactly?
I have posted multiple references on the use of AI in oncology; you make unsupported claims. ‘Plenty of researchers…’. Why not just say ‘some people say’.
You could have done a quick google search as easily as myself.
https://www.nature.com/articles/s41698-026-01276-6
AI is a game changer in oncology.
You haven’t read it, have you.
Hardly a game changer of the magnitude you think of. Moreover, CV is not generative. Pattern matching on X-rays has been common for a while, and has little to do with the current heavily marketed landscape of LLMs for everything.
This is one article. Are you actually interested in learning about the benefit of AI in cancer research? I could post a dozen articles, but would it make a difference to you? Also keep in mind it’s only going to get better as the models improve. I suspect your position is more ideological rather than rational.
https://acsjournals.onlinelibrary.wiley.com/doi/full/10.1002/cncr.70050
And I suspect your position comes from not doing any due diligence on the matter.
Funny that you call mine “ideological” though, since you are the one making claims without any substance, e.g. “it’s only going to get better”. How could you even know? Not even researchers at the very edge do. There have been concerns about the future availability and quality of data. Plenty of researchers have come forward pointing that poisoning a LLM is exceedingly easy. Really, how do you know that “it’s going to get better”? Explain that to me. What do you know that everybody else doesn’t?
How do you even know that AI, as we know it, it’s going to be revolutionary in the near future? Most people only know of technology successes because of survivorship bias, but I’ve been through several revolutions that faded out. How is this one different? And why would you think you’re right, when not even expert researchers are sure?
I’ve already provided two references. Please feel free to post the link supporting that AI has no influence in medicine.
You haven’t answered a single one of my questions.
I’m going to assume that you fell for the hype and know nothing of what you’re talking about.
Right. The NIH: National Cancer Institute is nothing but hype now. You need to expand your sources past Instagram.
https://www.sciencedirect.com/science/article/pii/S0304383526002569
“AI-powered platforms are now accelerating molecular subtyping, refining risk stratification, and supporting individualized therapeutic recommendations by jointly modeling imaging, tissue architecture, and molecular landscapes. Moreover, emerging virtual cell and mechanistic foundation frameworks introduce a new computational paradigm for simulating cellular responses and drug-tumor interactions, offering predictive insights for treatment design and drug discovery.”
Again, CV is not new. Computational biological simulation isn’t new either. More computational power and better algorithms have been a source of significant progress in healthcare for many decades now. If we go back twenty years, protein folding simulation was all the rage, but of course most people outside CompSci hadn’t heard of it.
I call the current AI “hype” because all these advancements have been going on for a while, but most people are catching up only now because they got hooked on marketing material they see on the news.
Anyway, I’m going to paste my message here once again.
Now, are you an AI researcher? What do you know about any of this, exactly?
I have posted multiple references on the use of AI in oncology; you make unsupported claims. ‘Plenty of researchers…’. Why not just say ‘some people say’.
Thanks. I’m done.