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Artificial intelligence better than humans at spotting lung cancer

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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%. These errors typically delay the diagnosis of lung cancer until the disease has reached an advanced stage when it becomes too difficult to treat. New research may safeguard against these errors.


Artificial intelligence system spots lung cancer before radiologists

#artificialintelligence

CHICAGO --- Deep learning - a form of artificial intelligence - was able to detect malignant lung nodules on low-dose chest computed tomography (LDCT) scans with a performance meeting or exceeding that of expert radiologists, reports a new study from Google and Northwestern Medicine. This deep-learning system provides an automated image evaluation system to enhance the accuracy of early lung cancer diagnosis that could lead to earlier treatment. The deep-learning system was compared against radiologists on LDCTs for patients, some of whom had biopsy confirmed cancer within a year. In most comparisons, the model performed at or better than radiologists. Deep learning is a technique that teaches computers to learn by example.


Artificial intelligence system spots lung cancer before radiologists

#artificialintelligence

CHICAGO --- Deep learning - a form of artificial intelligence - was able to detect malignant lung nodules on low-dose chest computed tomography (LDCT) scans with a performance meeting or exceeding that of expert radiologists, reports a new study from Google and Northwestern Medicine. This deep-learning system provides an automated image evaluation system to enhance the accuracy of early lung cancer diagnosis that could lead to earlier treatment. The deep-learning system was compared against radiologists on LDCTs for patients, some of whom had biopsy confirmed cancer within a year. In most comparisons, the model performed at or better than radiologists. Deep learning is a technique that teaches computers to learn by example.


AI can diagnose breast cancer more accurately than a doctor can

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Artificial intelligence can diagnose breast cancer more accurately than trained doctors, a study suggests. The research on almost 30,000 women who underwent screening found a computer programme could reduce the number of cases missed by more than two thirds. Researchers said the algorithmdeveloped by Imperial College London, Northwestern University in Chicago and Google Health was a "huge advance" in early detection of cancers. Breast cancer is the most common type of cancer in the UK, affecting around one in eight women - with 55,000 diagnoses annually and 11,000 deaths. Experts said the breakthrough could save thousands of lives, by finding deadly tumours that would otherwise go undetected.


Artificial Intelligence: Can It Improve Results of Cancer Screening Programs?

#artificialintelligence

Imaging studies are an important part of screening and diagnosis for some cancers, lung, and breast in particular. Such studies have led to more lung and breast cancers being diagnosed at a smaller size compared to what was found prior to the advent of screening programs. One important research question that is currently being explored is whether the use of artificial intelligence to aid in diagnosis can improve the performance of radiologists alone. Let's take a look at what we know so far. According to the American Cancer Society (ACS), approximately one in eight women will be diagnosed with breast cancer in their lifetime.