TRAINING PROCEDURE AND SYSTEM FOR ARTIFICIAL INTELLIGENCE INTENDED FOR THE ANALYSIS OF MAMMOGRAPHIC DATA FOR THE IDENTIFICATION OR EXCLUSION OF THE PRESENCE OF BREAST CANCER

Training procedure for artificial intelligence for mammographic data analysis for breast cancer detection including acquiring mammographic data from a plurality of sources and including mammographic images, report texts relating to images, and structured data obtained from SIO, EMR, BI-RADS and MOM including at least metadata relating to part of the images, processing mammographic data through algorithms implementing a multimodal deep neural network (DNN) developing a mammographic data analysis model by performing learning based on sub-phases of first multi-label classification of each image implemented through a model with Encoder-Decoder architecture based on convolutional neural network (CNN) and/or Transformers, association of parts of report texts with images and/or parts of structured data, implemented through a model with Encoder-Decoder architecture based on a bidirectional long-term memory (Bi-LSTM) and/or Transformers, second multi-label classification of mammographic structured data implemented through a model with Encoder-Decoder architecture based on CNN and/or Transformers.