Do not use the IBM only artificial intelligence to predict diabetes, where he developed researchers a model of AI that can predict breast cancer malignant within a year at a rate accuracy of up to 87 percent compared to scientists X-ray the humans, while there are already methods of prediction of the AI depend on X-rays of the breast or medical records, the contributions of IBM Models Own which you using both, and probably be more reliable as a result, it depends of the model on clinical data for medical histories for him and his family, which allows to create an algorithm with high accuracy relatively.
Says model also associating the data obtained by other functions in the person’s body, such as iron deficiency and the function of the thyroid gland, and IBM pulling data from laboratory tests and records of cancer diagnoses and other procedures through examinations which know not the person, all that gives great accuracy in the diagnostic process and that it is index can be ascertained by Tests other laboratory.
According to IBM, this model can be achieved from the diagnosis of the radiologist and reduce the chances of sending patients for tests, follow-up is not necessary cost more money and time, this may be particularly important in countries where a clear lack qualified staff, or in any location where there is no ample time to conduct tests human.
IBM system will be more comprehensive
IBM uses artificial intelligence to predict the breast cancer by 87%
IBM system is not only more forms to predict the breast cancer progress, where work by MIT developer the diagnosis of the disease before its appearance for up to five years in advance, using pictures only, however, IBM is betting on to follow a more holistic approach will be more important for clinicians, and it may be his approach is more a reflection on the population, simply by looking at the factors not associated with the transaction involving intercourse, in both cases there is a real possibility that more patients with cancer of the breast will start the treatment before the appearance of the first tumor.
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