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Individuals considered at high risk were 25 times more likely to develop pancreatic cancer within three years.
Clinical trials that test new cancer drugs or combinations seldom account for other medications a patient may be taking.
AI tools have the potential to make cancer imaging faster, more accurate and even more informative. And that’s generating excitement.
P-NET is a “biologically informed deep learning model” capable of guessing a prostate cancer patient’s disease state.
Images used to train artificial intelligence to diagnose skin cancer rarely include non-white people.
Highlights from the over 400 abstracts related to colorectal cancer presented at The American Society of Clinical Oncology’s annual meeting
A novel artificial intelligence device known as GI Genius could detect precancerous polyps that clinicians may otherwise overlook.
The GI Genius aids clinicians in detecting potential irregularities during colon cancer screening and surveillance.
An inside look at five research developments that have the potential to transform the treatment of cancer
Artificial intelligence may help predict response to immune checkpoint blockade in patients with metastatic melanoma
Combining machine learning with cell engineering, scientists can design ‘living medicines’ that precisely target tumors
Enrica Quattrocchi, MD, examines cutaneous melanoma by applying AI to distinguish between slow growing and aggressive melanomas.
Joann Elmore, MD, MPH, is working to improve the accuracy and consistency of melanoma diagnoses
Pacific NW cancer centers and Microsoft aim to accelerate research by helping data flow.
“This technology could help inform how aggressive or conservative surgery needs to be.”
This technological advancement could help make up for a shortage in radiologists in the United Kingdom in particular.
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