Artificial intelligence helps to diagnose lung cancer during experiments

An innovative algorithm with a highly diagnostic artificial intelligence contributed to improving the performance of a radiologist in the detection of lung cancer by reading X -Rays, according to a study published in the “Radoli” journal. The study, conducted at the South Korean University of Sol, has monitored an increase in ‘experts’ acceptance of proposals for artificial intelligence’. Adopting proposals for artificial intelligence by the radiologist is an important issue in the integration of technology successfully into clinical practice, and to make acceptance, the artificial intelligence algorithm delivered transparent and interpretable outputs, as well as effectively informed about uncertainty, and showed consistent reliability. Artificial intelligence -algorithms can provide an accurate diagnosis of radiology, but factors that influence the extent of the acceptance of radiologists to the results of reading images using artificial intelligence “are still unclear.” The researchers at the University of Seoul considered how these factors affected the discovery of malignant lung knobs or lung cancer, while reading X -Rays with the help of artificial intelligence. During the study, 30 specialists, including 20 breast specialists with an experience of 5 and 18 years, and 10 residents of the rays two years to only three years of experience, who evaluated 120 radial photos of chest without artificial intelligence. Of the 120 radial chest images evaluated, there were 60 people suffering from lung cancer and 60 controls. The average age of patients was 67 years. In a second session, each group has an interpretation of X -Ray using artificial intelligence with a high resolution or low resolution. Data and artificial intelligence analysis with a high resolution is an algorithm that shows a high level of accuracy and reliability in medical diagnoses, specially designed to analyze medical data, such as photos or records of patients, and provide diagnostic predictions or assistance to a health care person. To achieve a high diagnostic performance, artificial intelligence -algorithms often benefit from deep learning techniques, and these algorithms can learn from large -scale data collections, which extract complicated patterns or functions from medical images or other types of data. The use of artificial intelligence with a high resolution improved the performance of the discovery of radiologists, more than low -precision artificial intelligence, and also led to more frequent changes in expert definitions, a concept known as the ability to influence. The ability to influence is the increase in the possibility of changes in expert decisions when using artificial intelligence algorithms with a high -resolution in the diagnosis process. When you integrate artificial intelligence into the operation of radiology to make suggestions or highlight the fields of interest, it can affect the radiologist’s decision. The researchers say that the relatively large sample size in this study has strengthened the confidence of experts in artificial intelligence proposals. The study reported that people are more likely to be influenced by artificial intelligence if they are highly diagnostic performance. The study said that the integration of artificial intelligence algorithms into the work of a radiologist can make valuable suggestions, or emphasize the areas of potential interest in X -ray images. It can also improve reducing monitoring errors, improve allergies and increase the accuracy of comprehensive diagnosis. Also read: