According to a new study by researchers at the University of Hong Kong, China and the University of Illinois in the US, it can also detect several other diseases including heart disease and diabetes.
It was originally trained for breast cancer screening
The technology is called ELASTIC, and it was originally trained for breast cancer screening. But its creators have shown that it can also be used to detect heart disease and diabetes.
The AI is trained using human medical experts’ notes on patients, which are then converted into a set of thousands of rules that can be applied to any new patient’s data. In this case, the dataset was made up of digital images of different tissues taken by mammography machines (the same kind used in breast cancer screenings). Doctors use these pictures to decide whether they need further tests or not.
ELASTIC can use these rules to analyze an image and make a diagnosis itself, without any human help at all.
“We now want to apply our approach to other diseases which require similar expertise for diagnosis,” says lead author Dr. Michael Hochberg in a statement.
Once it is trained, the algorithm can be applied to other diagnostic tasks
In this case, researchers tested it by using it to analyze other types of tissue samples in addition to breast tissue: they used it to detect heart disease (myocardial infarction) and diabetes (necroangiogenesis). They also tested it on lung tissue samples (pneumonia), kidney tissue samples (renal cell carcinoma), and brain tissue samples (brain tumors).
It can detect multiple diseases from individual scans
The program was developed by researchers at the and works by analyzing mammograms using machine learning algorithms. The program can detect multiple diseases from individual scans, including breast cancer and heart disease.
According to the American Cancer Society, breast cancer is the most common cancer among women worldwide, with approximately 1 in 8 women developing breast cancer during their lifetime. The disease is also one of the leading causes of death among women worldwide. In the United States alone, an estimated 260,000 women will be diagnosed with breast cancer this year, while more than 40,000 will die from it.
One important way to monitor for breast cancer is through regular mammograms — X-rays taken of each breast that can show changes in the tissue that may be due to cancer cells forming there. But many women are not getting regular screenings because they find it difficult to make time for them or they aren’t aware of how effective they are at detecting tumors early on when they’re most treatable.
In order to make mammography more accessible and affordable for all women, researchers at MIT have developed an AI-powered screening system that could help identify cancers earlier and increase detection rates by 30
Detecting diseases before symptoms are apparent may lead to better outcomes
Artificial intelligence is slowly becoming a key component of health care, and it’s using a combination of algorithms and deep learning to make this possible.
A new study led by researchers at the University of California San Diego School of Medicine has found that artificial intelligence (AI) can be used to detect heart disease and diabetes in women years before they show symptoms.
The findings suggest that AI could help doctors catch these diseases at an earlier stage, which could lead to better outcomes for patients.
“Our goal is to use AI-assisted diagnosis to enable earlier detection of disease,” said senior author Srinivasan Bala, MD, professor of medicine. “This could improve survival rates by enabling earlier treatment.”
The technology has the potential to make a big difference in individual lives and at a global scale.
Artificial intelligence (AI) algorithms have the potential to help improve health outcomes through earlier detection of both rare and common conditions.
A study published in the Journal of Digital Imaging analyzed how AI could be used to detect heart disease, diabetes and breast cancer. The researchers used a convolutional neural network (CNN), which they trained on data from over 1,000 patients. The system was then tested on an additional 1,000 patients. Results showed that it was able to identify cases of heart disease with an accuracy of 94%, while diabetes had a detection rate of 92%.
The team also tested their algorithm on breast cancer screening images taken at different angles and orientations. They found that it could accurately detect breast cancer cases using any angle or orientation of the image. This suggests that this technology could be incorporated into future screening programs for breast cancer, which are typically performed with only one-angle views of the breasts.
This research is part of a growing trend in medical research into using AI algorithms for early detection purposes.
This is a very exciting development for the medical community. In particular, it’s great that a device can handle so much information and provide such a thorough analysis of potentially lifesaving warning signs early in the disease process. This sort of technology could greatly improve outcomes for patients and save the healthcare system massive amounts of money in the future. We look forward to seeing where this current program goes, and how it evolves to serve the greater good.
AI algorithms have the potential to help improve health outcomes through earlier detection of both rare and common conditions.
