Interesting >>>> Artificial intelligence and disease diagnosis

Artificial intelligence and disease diagnosis.

Developments in the field of artificial intelligence are expanding the boundaries of their practical application. Neural networks are a learning system that can use its capabilities indefinitely. Having tested the work of neural networks in various technical industries, scientists have come to the conclusion that neural networks are good diagnosticians.

As you know, a timely detected disease increases several times a person's chances of cure and survival, especially when it comes to oncological diseases.

As studies of several foreign start-ups have shown, neural networks are able to optically (in terms of human qualities - visually) identify areas of tissue affected by cancer from images, and do this with an accuracy approaching one hundred percent.

For comparison, a doctor-diagnostician who studies a patient's image until the moment of laboratory detection based on a biopsy of tissue areas susceptible to carcinogenesis determines oncology with an accuracy of at least 70%, while artificial intelligence, which was offered for preview and training several hundred computed tomography images with an already known tissue pathology (malignant formations), studying images with undiagnosed pathologies, is able to determine a cancer at the initial stages of its development with an accuracy of about 90%.

Artificial intelligence is also convenient in cases when diagnostics are carried out directly during the examination of tissues, for example, during colonoscopy or endoscopy.

But in each barrel of honey, as a rule, there is also its own fly in the ointment. It turned out that in fact, neural networks are considered all oncopathologies as malignant and cannot distinguish between malignant and benign processes. It is no longer possible to do without human intelligence and laboratory research. But the merit of artificial intelligence in the field of cancer diagnostics gives a chance for early diagnosis of cancer, which is much more important than its subsequent differentiation by the degree of malignancy, which is easy for a doctor to cope with.

How are artificial intelligence and disease diagnostics combined in practice? Researchers of the diagnostic capabilities of artificial intelligence hope to combine the skills of neural networks and the experience of doctors by creating diagnostic automation - it is only necessary to methodically collect a base of photographic and video recording of hardware diagnostics so that artificial intelligence has the opportunity to learn from the collected data.