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New artificial intelligence system launched to detect abnormalities in chest X-rays

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New artificial intelligence system launched to detect abnormalities in chest X-rays

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Pablo Valdés and Rodrigo de Luis analyze the "utility" and "conflicts" of IA in radiology.

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Pablo Valdés and Rodrigo de Luis analyze the "utility" and "conflicts" of IA in radiology.

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"Implementing an IA system involves important validation work and not all Radiology services have sufficient knowledge or means"

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"Implementing an IA system involves important validation work and not all Radiology services have sufficient knowledge or means"

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IA, both in Radiology and in other areas of Medicine and Biology, has served to accelerate advances in knowledge of the disease (Covid-19) and its solutions, su

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Artificial intelligence in Radiology during the Covid-19 pandemic

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Artificial intelligence in Radiology during the Covid-19 pandemic

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At the beginning of the pandemic, automatic systems appeared capable of “automatically” diagnosing Covid-19 from chest x-rays or CT scans, or detecting pneumonia caused by this disease and “distinguishing” it from other types of pneumonia. However, when CRP became the "gold standard" for diagnosis, interest shifted to more focused on analyzing patient outcomes, trying to predict things like need for a ventilator or admission to the ICU.

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Advantages and disadvantages of artificial intelligence in radiology.

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Advantages and disadvantages of artificial intelligence in radiology.

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The main disadvantages of AI today applied to radiology are the following:

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The main disadvantages of AI today applied to radiology are the following:

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-The need for access to large image banks.
-Data processing: although there are now abundant sources of images such as PACS systems, the images must be processed before being used to train the network.
-Medical-legal responsibilities: if the diagnosis is not made by a human being, the question arises as to who is responsible for that diagnosis.

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-Detection of very specific elements in radiological images, for example, microcalcifications in a mammogram.
-Radiomics, It consists of an initiative that tries to extract the maximum possible characteristics from an image of a specific pathology.
-Biobanks seek more efficient image storage avoiding the problems derived from PACS overload.

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What radiologists should know about artificial intelligence

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What radiologists should know about artificial intelligence

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Artificial intelligence (AI) is one of the fastest growing areas in the field of computational sciences and has a great impact on radiology, so it is extremely important for radiologists to consider its possible applications and the ethical problems derived from the use of these systems.

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Radiology is a very complex specialty, with a strong clinical focus, in which the radiologist performs many tasks and has competencies in different fields. The diagnosis of pathology is one of them. Having advanced tools that enhance their capacity is something that all patients will benefit from. That is why we speak of 'assisted intelligence', as a scenario in which radiologists will have tools that will prevent us from performing repetitive tasks, with the possibility of error, and that will allow us to do what we should do: think about the patient and see each case globally.

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Assuming that radiologists or radiology will disappear is like assuming that calculators can make engineers disappear (something that was once considered).

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It can help in diagnosis, but also go further in applications such as predicting the evolution of a patient, or the early detection of anomalies that can lead to a pathology," he said.

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Information that exists in the images but is imperceptible to the human eye can be extracted, massively analyzed and combined with other sources of information.

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It consists of automating time-consuming processes that machines can learn to do very well, such as segmenting lesions or structures of interest in a medical image.

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"It can improve patient appointments, facilitate the technician in image placement and acquisition, improve radiological technique, decrease acquisition times, radiation doses or contrast doses

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"AI can help clinicians order the best imaging technique for each patient."