Google announced that it has licensed its artificial intelligence technology to iCAD, a company whose services are primarily established around breast cancer detection in healthcare settings. iCAD has already included its AI strategies for its cancer screening services, but now it will also include the Google algorithm that Google built with a team of researchers from Northern University. Google’s mammography algorithm outperformed radiologists in terms of registering fewer false positives and false negatives when reading images.
The study included mammograms of more than 91,000 women in the US and UK. The machine learning algorithm also reduced false positives by 9% in the US and almost 3% in the UK. It was mentioned that Google’s algorithm incorporates a large number of images beyond breast tissue to refine the machine learning process. This facility is now commercially available worldwide for the 7,500 mammography sites whose services are based on iCAD. Under the partnership agreement, the technology will be developed and refined by iCAD and Google.
This algorithm can ease the burden on radiologists; however, it cannot replace radiologists, at least not in the near future. It is also expected that the AI-based system will make mammography accessible to more people around the world, especially in low-resource areas that cannot support the infrastructure required to house the equipment. storage of mammography images.
iCAD plans to integrate Google’s AI-based mammography research model into existing tools. The first is its “ProFound AI” tool, which analyzes images from Digital Breast Tomosynthesis (DBT) (3D mammography). The tool looks for malignant soft tissue densities and calcifications in DBT images. This tool can also provide a personalized breast cancer estimate for each individual.
The more data from mammograms are fed into the algorithm, as with any machine learning system, the more refined it becomes to detect the minute differences that distinguish normal tissue from potentially cancerous tissue. Women who undergo mammograms using the AI-based system will have their data returned to the algorithm without any identifying information. Right now, most women getting mammograms are probably unaware that an AI system can work in the background, supplementing the radiologist, because no regulatory agency has approved interpretation of mammograms entirely based on the AI.
These types of machine-based systems can detect patterns invisible to the human eye. The current AI algorithm used by iCAD can detect even minute calcifications in breast tissue that could lead to an increased risk of heart disease. If this link is confirmed, mammograms could be used to assess the risk of heart disease in women. Including an AI perspective in mammograms could help improve how breast cancer risk in women is determined.
AI systems, for example, can better distinguish differences specific to specific racial and ethnic groups; for example, African American women, US women are more likely than other women to develop more aggressive types of breast cancer and die from the disease, so training an AI system to detecting and detecting these cancers early can result in better outcomes. If an AI algorithm detects these differences, women may be referred for further testing to determine if they are at higher risk of developing cancer. This could help them get treatment sooner, giving them a better chance of survival. It could also mean less expensive medical services, which would lead to savings in health care costs.
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Avanthy Yeluri is a dual degree student at IIT Kharagpur. She has a keen interest in data science due to its wide applications in a variety of industries, as well as its cutting-edge technological advancements and how they are used in daily life.
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