Deep learning modeling using health screening images

A method for improving breast cancer screening using artificial intelligence (AI), comprising:

• receiving a user image by an AI system, the AI system including:
• a first AI model trained using labeled training images including images from prior mammograms to predict cancer, and
• a second AI model trained using labeled training images including images from current mammograms to classify mammogram images, wherein the second AI model is initialized using the weights of the first AI model using transfer learning;
• and
• receiving a classification output indicating a likely current breast cancer diagnosis or a likelihood of the user to develop breast cancer in the future.

A method for training an artificial intelligence (AI) system for improved health screening, the method comprising:

• receiving training images, wherein each of the training images is linked in a group, and wherein the group includes training images of one training user;
• registering grouped training images, wherein registering grouped training images involves aligning a first training image so that the same region of 2D space in the first training image in the group can be compared to a same region of 2D space in a second training image in the group;
• obtaining a first set of feature vectors from a first AI model trained to predict cancer using training images from prior mammograms;
• obtaining a second set of feature vectors from a second AI model trained to classify images using training images from current mammograms;
• applying a feature selection algorithm to the first set of feature vectors and the second set of feature vectors;
• inputting feature vectors selected using the feature selection algorithm into a classification AI model;
• and
• providing an output, wherein the output includes a first prediction score indicating a likelihood of future breast cancer development and a second classification score indicating likelihood of current cancer.

A system comprising:

• a memory;
• and
• a processor in communication with the memory, the processor being configured to perform operations comprising:
• receiving training images, wherein each of the training images is linked in a group, and wherein the group includes training images of one training user;
• obtaining a first set of feature vectors from a first AI model trained to predict cancer using training images from prior mammograms;
• obtaining a second set of feature vectors from a second AI model trained to classify images using training images from current mammograms;
• applying a feature selection algorithm to the first set of feature vectors and the second set of feature vectors;
• inputting feature vectors selected using the feature selection algorithm into a classification AI model;
• and
• providing an output, wherein the output includes a first prediction score indicating a likelihood of future breast cancer development and a second classification score indicating likelihood of current cancer.

A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform operations, the operations comprising:

• receiving training images, wherein each of the training images is linked in a group, and wherein the group includes training images of one training user;
• obtaining a first set of feature vectors from a first AI model trained to predict cancer using training images from prior mammograms;
• obtaining a second set of feature vectors from a second AI model trained to classify images using training images from current mammograms;
• applying a feature selection algorithm to the first set of feature vectors and the second set of feature vectors;
• inputting feature vectors selected using the feature selection algorithm into a classification AI model;
• and
• providing an output, wherein the output includes a first prediction score indicating a likelihood of future breast cancer development and a second classification score indicating likelihood of current cancer.