Sanjay K. Juneja, MD, discusses how artificial intelligence has evolved in 2024 to help improve early detection of cancer.
Sanjay K. Juneja, MD, hematologist & medical oncologist at Mary Bird Perkins Cancer Center, discusses how artificial intelligence has evolved in 2024 to improve early detection of cancer.
Transcription:
0:10 | Artificial intelligence has really given us reason for hope when it comes to detection earlier in cancers, which obviously the hope is that they get cured quicker. I guess there are several examples. One is where they were looking at pancreatic cancer. That's pretty exciting. It was, I think, North Well, Northwell Health and using kind of ai, ai powered technology with MRI and CT scans, what you can do is you can appreciate changes that may be really challenging to notice with the naked eye, right? Just some pixelated changes or things that are happening in the architecture. We are talking about, subtleties so small that it takes something like artificial intelligence kind of powering to compare a whole bunch of things that happened in the past, and then knowing that they turned out to be cancer, that is what primes this AI technology to say, I have seen that before, and I know that X amount of time it actually turns into invasive pancreatic cancer, and is able to clue you in sooner.
1:17 | I think that's the concept behind AI excitement, especially when it relates to imaging, because a lot of times, if you think about it, radiologists do not always get the benefit of seeing a serial number of radiology images and comparing them, knowing kind of at the top of mind that they are all the same patient. They may pull up a previous scan, but that gets very exciting.
1:42 | There are all kinds of imaging that AI is helping to notice these things, especially with breast cancer. There is also technology that's coming out to be able to increase both the sensitivity, so how easily or quickly you can appreciate something while scanning the or doing a mammogram or screening for breast cancer, but also the specificity. A lot of these kinds of false positives or concerns where we end up doing invasive procedures, causes a lot of stress and anxiety. Those can really be reduced by having better imaging techniques. Then, there are a whole bunch of other examples when it comes to AI imaging.
Advancing Neoadjuvant Therapy for HER2+ Breast Cancer Through ctDNA Monitoring
December 19th 2024In an interview with Targeted Oncology, Adrienne Waks, MD, provided insights into the significance of the findings from the DAPHNe trial and their clinical implications for patients with HER2-positive breast cancer.
Read More
AI-Driven Deep Learning Model Shows Promise in Standardizing MDS Diagnosis
December 10th 2024In an interview, Palak Dave discussed how artificial intelligence, using deep learning to analyze bone marrow aspirate smear images, could standardize and accelerate the diagnosis of MDS vs pre-MDS conditions.
Read More
Systemic Therapy Choice Linked to Radiosurgery Outcomes in Brain Mets
December 6th 2024In an interview with Targeted OncologyT, Rupesh Kotecha, MD, discussed a study focused on how systemic therapy selection impacts outcomes in patients with brain metastases, particularly those with lung cancer.
Read More