AI can predict pancreatic cancer three years ahead of humans:
AI algorithms can screen for pancreatic cancer and predict whether patients will develop the disease up to three years before a human doctor can make the same diagnosis, according to research published in Nature on Monday.
Pancreatic cancer is deadly; the five-year survival rate averages 12 percent. Academics working in Denmark and the US believe AI could help clinicians by detecting pancreatic cancer at earlier stages, if the software can reliably predict which patients are at higher risk of developing the disease.
The researchers trained AI algorithms on millions of medical records obtained in the Danish National Patient Registry and the US Veterans Affairs Corporate Data Warehouse. The models were trained to correlate diagnosis codes – labels used by hospitals describing different medical conditions – to pancreatic cancer.
[...] "Cancer gradually develops in the human body, often over many years and fairly slowly, until the disease takes hold," Chris Sander, the study's co-senior investigator and leader of a lab working at the Department of Systems Biology at Harvard Medical School, told The Register.
"The AI system attempts to learn from signs in the human body that may relate to such gradual changes."
[...] The most effective model, based on a transformer-based architecture, showed that out of the top 1,000 highest-risk patients over 50, about 320 would go on to develop pancreatic cancer. The model is less accurate when trying to predict pancreatic cancer over longer time intervals compared to shorter ones, and for patients younger than 50.
"AI on real-world clinical records has the potential to produce a scalable workflow for early detection of cancer in the community, to shift focus from treatment of late-stage to early-stage cancer, to improve the quality of life of patients and to increase the benefit/cost ratio of cancer care," the paper reads.
Effective prediction in real-world settings will rely on the quality of patients' medical histories. Future AI-based screening tools for pancreatic cancer will have to be trained on specific local population data, the study found. A model trained on data from Danish patients, for example, was not as accurate when applied to US patients.
"Given the experience in Denmark and one or two US health systems, this means that in each country with different conditions and different systems, it is best to re-train the model locally. AI needs a lot of data to train. Access in different locations is not straightforward, as medical records are and should be confidential. So local approval and data security is essential," Sander said.
The study is still in its early stages, and the software cannot yet be used to run screening programs. Improvements are needed before even a trial can be conducted.
(Score: 1, Interesting) by Anonymous Coward on Thursday May 11, @08:25AM (1 child)
(Score: 3, Interesting) by shrewdsheep on Thursday May 11, @11:51AM
The paper claims an AUC of 0.88 (1 being perfect prediction) which is a combined measure of sensitivity and specificity. 0.88 is very good but such studies, and this one is no exception, only consider internal consistency using a data split. In different settings (different hospitals in different countries) accuracy can drop dramatically.
(Score: 2) by krishnoid on Thursday May 11, @06:12PM
You know where this is going [youtu.be].
I thought "pancreatic cancer" had multiple kinds, though -- aggressive, typical ones and then slow one that Steve Jobs died from. Still, it's great that these sorts of things can be identified from data-mining the common blood and urine (and saliva and fecal, maybe eventually) analyses over time rather than via biopsy.
(Score: 2) by DannyB on Friday May 12, @02:21PM
If an AI predicts your pancreatic cancer, and the prediction turns out to be true, then shouldn't they be able to bill your insurance a gigantic amount for the valuable medical service they provided?
How often should I have my memory checked? I used to know but...