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Cutting-edge technology of Artificial Intelligence for Cancer Detection

artificial intelligence for cancer detection

AI has induced the mass of technology driven people to gaze at and be astonished at the marvels that it has created in the field of cancer detection. Cancer that has been known to spread in the current era like fire in the forest has killed millions of people across the globe. And the reason to lament is that there is almost no possibility for the person to live if he has been afflicted by cancer. The only possibility of survival arises when the disease is detected at the earliest stage possible. Standard screening methods can most of the time miss signs of cancer and this is why people are now following the footsteps of AI as far as detecting cancer is concerned.

Creating benchmarks:

AI is all about making a smart choice that can eliminate the traditional cancer detection methods like CT scan or the hereditary testing method that have failed miserably in the past few years to detect cancer. Some methods to detect cancer in the modern contemporary scenario of health are mentioned below that prove AI’s worth over human methods:

  • Google researchers in association with the Northwest Medicine have created an AI model that is 100% capable of detecting lung cancer from screening tests. You will be stunned to know that the results are even better than human radiologists with an average of eight years experience.
  • To be very specific AI techniques use 3D volumetric deep learning to scrutinize the entire anatomy on chest Computer Tomography scans, as well as patches that identify regions with malignant as well as benign lesions. With the mammography images you can detect the lung and breast cancer for finding out the cancer before it has affected the normal cells and prevented their contact inhibition property.
  • Apart from that LUNIT founded by six deep-learning experts from the South Korean university in 2013 has been trained impressively to get an INSIGHT algorithm on chest x-rays and mammography images to detect lung and breast cancer. Lunit’s CEO Brandon Suh tells that rather than guiding our algorithm to a specific location, we provided a region and said “there is a nodule there, try to find it,” and let the algorithm learn by itself,’. It is extremely difficult for doctors to find small nodules. But with the algorithm you can profoundly be assured of the fact that it searches exhaustively for cancer patterns to dramatically reduce the chance of a false, negative or missed case of cancer.

The bottom line:

The model by the Google researchers detected cancer 5% more often on average than a group of six human experts and was 11% more likely to reduce false positive consequences. AI thus has not only increased the efficiency but also the accuracy of cancer detection tests more than the traditional methods. As per the journal Nature Medicine, AI can significantly help to generate a lung cancer malignancy risk score for the patient along with identifying the location of the malignant tissue in the lungs.

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