Release date: 2016-09-06 A new study shows that artificial intelligence helps to better understand the results of lung function tests in the diagnosis of long-term lung disease. The results of the European Respiratory Society's International Conference on September 4, 2016 showcased this achievement, the first exploration of the potential application of artificial intelligence in improving the diagnostic accuracy of lung diseases. Current tests require a range of methods, including a lung function test that measures the amount (volume) and velocity (flow) of air during breathing, followed by a plethysmographic test that measures static lung volume and airway resistance, and finally a diffusion test. , measuring the amount of oxygen and other gases that travel through the alveoli. The analysis of these test results is mostly based on expert opinions and international guidelines, trying to detect images in the results. In this new study, the researchers collected data from 968 experimenters who were the first to perform a complete lung function test. All participants received the first clinical diagnosis based on lung function tests and all other necessary additional tests (eg CT scans, electrocardiograms, etc.). The final diagnosis will also need to be verified by medical experts. The researchers then explored whether the concept of "machine learning" could be used to analyze a complete lung function test. Using machine learning algorithms, you can learn and perform predictive data analysis. The team developed an algorithm that incorporated routine lung function parameters and clinical variables such as smoking history, body mass index, and age. Based on clinical and pulmonary function data, the algorithm makes the most likely diagnostic recommendations. Wim Janssens of the University of Leuven in Belgium, a senior member of the study, said: "We have proven in this new study that artificial intelligence can provide us with a more accurate diagnosis. The significance of our algorithm is that it can be a more The standard objective, non-biased approach, simulates the complex reasoning process that clinicians use for diagnosis." Currently, clinicians must rely on population-based parametric analysis. With artificial intelligence, the machine can view a collection of all images at once, which helps to produce a more accurate diagnosis. This has been seen in other health areas, automatically interpreting the ECG results that are commonly used in clinical practice as a decision support system. Marko Topalovic, the first author of the study, from the University of Leuven, Belgium, said: "The advantage of this method is that it can more accurately and automatically explain the results of lung function tests to better detect the disease. This can not only help to have no experience. The clinician has many benefits for the entire medical profession because it saves time in completing the final diagnosis and reduces the extra testing that clinicians are using to confirm the diagnosis." The team's next step is to test the algorithm in different populations and improve system decision making and lung function verification by continuously updating clinically diagnosed lung function data. Source: Lei Feng Net enous catheter set,central venous catheter price,central venous catheter kit,central venous catheter triple lumen Anesthesia Medical Co., Ltd. , https://www.sinoanesthesia.com
The latest application of artificial intelligence! Improve lung diagnosis accuracy
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