Tag: artificial intelligence

Categories : Cancer Expert OpinionTags :

To Properly Use AI to Analyse Breast Cancers, Look to Past Mistakes

On By ModernMedia
Source: National Cancer Institute

Doctors writing in an editorial in JAMA Health Forum caution that while using AI to analyse breast cancer tumours has the potential to improve healthcare efficiency and outcomes, similar technological leaps have previously led to higher rates of false-positive tests and over-treatment.

The editorial wasco-written by Joann G. Elmore, MD, MPH, professor of medicine at the David Geffen School of Medicine at UCLA, and Christoph I. Lee, MD, MS, MBA, a professor of radiology at the University of Washington School of Medicine.

“Without a more robust approach to the evaluation and implementation of AI, given the unabated adoption of emergent technology in clinical practice, we are failing to learn from our past mistakes in mammography,” the authors wrote.

One of those “past mistakes in mammography,” the authors said, was adjunct computer-aided detection (CAD) tools, which grew rapidly in popularity in the field of breast cancer screening starting more than two decades ago. CAD was approved by the FDA in 1998, and by 2016 more than 92% of U.S. imaging facilities were using the technology to interpret mammograms and hunt for tumours. However, CAD did not improve mammography accuracy., according to the evidence. “CAD tools are associated with increased false positive rates, leading to overdiagnosis of ductal carcinoma in situ and unnecessary diagnostic testing,” the authors wrote. The US Medicare system stopped paying for CAD in 2018, but by then the tools had run up more than $400 million a year in wasted health costs.

“The premature adoption of CAD is a premonitory symptom of the wholehearted embrace of emergent technologies prior to fully understanding their impact on patient outcomes,” Drs Elmore and Lee wrote. “As AI algorithms are increasingly receiving FDA clearance and becoming commercially available with ROC curves similar to what we observed prior to CAD clearance and adoption, how can we prevent history from repeating itself?”

The doctors suggest a number of safeguards to avoid “repeating past mistakes” such as tying reimbursement to proven efficacy.

Source: UCLA Health

Categories : AgeingTags :

AI Model Identifies Compounds That Could Extend Life

On By ModernMedia
Photo by Tara Winstead from Pexels
Photo by Tara Winstead from Pexels

The University of Surrey has developed an artificial intelligence (AI) model that identifies chemical compounds that promote healthy ageing, which could help the development of pharmaceuticals for human lifespan extension.

In a paper published in Scientific Reports, a team of chemists from Surrey built a machine learning model based on the information from the DrugAge database to predict whether a compound can extend the life of Caenorhabditis elegans, a translucent worm whose metabolism is similar to humans. Because the worm has such a short lifespan, the researchers were able to test the effectiveness of the compounds.

The AI model identified three compounds that have an 80 percent chance of increasing the lifespan of elegans:

  • flavonoids (anti-oxidant pigments found in plants that promote cardiovascular health, examples include certain spices and herbs),
  • fatty acids (such as omega 3), and
  • organooxygens (compounds that contain carbon to oxygen bonds, such as alcohol).

Co-author Sofia Kapsiani, final year undergraduate student at the University of Surrey, said: “Ageing is increasingly being recognized as a set of diseases in modern medicine, and we can apply the tools of the digital world, such as AI, to help slow down or protect against ageing and age-related diseases. Our study demonstrates the revolutionary ability of AI to aid the identification of compounds with anti-aging properties.”

Commenting on the research, lead author Dr Brendan Howlin, Senior Lecturer in Computational Chemistry at the University of Surrey, said: “This research shows the power and potential of AI, which is a specialty of the University of Surrey, to drive significant benefits in human health.”

Source: SciTech Daily

Journal information: “Random forest classification for predicting lifespan-extending chemical compounds” by Sofia Kapsiani and Brendan J. Howlin, 5 July 2021, Scientific Reports.
DOI: 10.1038/s41598-021-93070-6