Researchers have used a deep-learning algorithm to detect lung cancer accurately from computed tomography scans. The results of the study indicate that artificial intelligence can outperform human evaluation of these scans. The condition is the leading cause of cancer-related death in the U.S., and early detection is crucial for both stopping the spread of tumors and improving patient outcomes. As an alternative to chest X-rays, healthcare professionals have recently been using computed tomography (CT) scans to screen for lung cancer. In fact, some scientists argue that CT scans are superior to X-rays for lung cancer detection, and research has shown that low-dose CT (LDCT) in particular has reduced lung cancer deaths by 20%.
The singer celebrated her 36th birthday at the Made in America festival in Philadelphia on Sunday, with festivities that included an extravagant birthday cake and a serenade from husband Jay-Z. The cake, made by Cake Life Bake Shop in Philly, cost at least an eye-watering $3,500, a source told Page Six on Wednesday. The cake shop's geode cakes "start at $3,500 and go up in price depending on detail, complexity, and size," they said. With such a hefty price tag it should come as no surprise that a lot of time and effort went into the dessert. "Obviously we were looking at [inspiration] and things like that, but making the cake is a two-day process," co-owner of Cake Life Bake Shop, Lily Fischer, told us.
To apply artificial intelligence to the task, the authors of the Nature report used mammograms from about 76,000 women in Britain and 15,000 in the United States, whose diagnoses were already known, to train computers to recognize cancer. Then, they tested the computers on images from about 25,000 other women in Britain, and 3,000 in the United States, and compared the system's performance with that of the radiologists who had originally read the X-rays. The mammograms had been taken in the past, so the women's outcomes were known, and the researchers could tell whether the initial diagnoses were correct. "We took mammograms that already happened, showed them to radiologists and asked, 'Cancer or no?' and then showed them to A.I., and asked, 'Cancer, or no?'" said Dr. Mozziyar Etemadi, an author of the study from Northwestern University. This was the test that found A.I. more accurate than the radiologists.
While there has been controversy over when and how often women should be screened for breast cancer using mammograms, studies consistently show that screening can lead to earlier detection of the disease, when it's more treatable. So improving how effectively mammograms can detect abnormal growths that could be cancerous is a priority in the field. AI could play a role in accomplishing that--computer-based machine learning might help doctors to read mammograms more accurately. In a study published Jan. 1 in Nature, researchers from Google Health, and from universities in the U.S. and U.K., report on an AI model that reads mammograms with fewer false positives and false negatives than human experts. The algorithm, based on mammograms taken from more than 76,000 women in the U.K. and more than 15,000 in the U.S., reduced false positive rates by nearly 6% in the U.S., where women are screened every one to two years, and by 1.2% in the U.K., where women are screened every three years.
Artificial intelligence is better than specialist doctors at diagnosing lung cancer, a US study suggests. The researchers at Northwestern University in Illinois and Google hope the technology could boost the effectiveness of cancer screening. Finding tumours at an earlier stage should make them easier to treat. The team said AI would have a "huge" role in the future of medicine, but the current software is not yet ready for clinical use. The study focused on lung cancer, which kills more people - 1.8 million a year - than any other type of cancer.