Efficient artificial intelligence analysis of radiographic images with combined predictive modeling

A system for analyzing images of a subject, the system comprising:

• a receiver to receive an image of the subject;
• at least one processor to automatically run an image identification and processing algorithm to identify, crop, orient and label at least one body region in the image to obtain a sub-image;
• at least one artificial intelligence processor to evaluate the sub-image;
• and a device to display the sub-image and evaluated artificial intelligence result.

A method for identifying and diagnosing a presence of a disease or a condition in at least one image of a subject, the method comprising:

• classifying the image to one or more body regions, labelling and orientating the image using a sub-image processor to obtain a classified, labeled and oriented sub-image;
• directing the sub-image to at least one artificial intelligence (AI) evaluation processor to obtain an evaluation result, and comparing the evaluation result to a database with evaluation results and matched written templates or at least one dataset cluster to obtain at least one cluster result;
• measuring the distance between the cluster result and the evaluation result to obtain at least one cluster diagnosis using a synthesis processor;
• and
• assembling the cluster diagnosis to obtain a report thereby identifying and diagnosing the presence of the disease or the condition in the subject.

A system for diagnosing a presence of a disease or a condition in an image and/or a medical result, of a subject, the system comprising:

• a receiver to receive an image and/or the medical result of the subject;
• at least one processor to automatically run an image identification and processing algorithm to identify, crop, orient and label at least one body region in the image to obtain a sub-image;
• at least one artificial intelligence processor to evaluate the sub-image and/or the medical result and obtain an evaluation result;
• and at least one diagnostic artificial intelligence processor to automatically run a cluster algorithm to compare the evaluation result to obtain a cluster result, measure distance between cluster result and a previously created cluster result from a specific dataset defined by one or more variables, evaluation result to obtain cluster diagnosis, and assemble a report.

A method for diagnosing a presence of a disease or a condition in at least one image of a subject, the method comprising:

• classifying the image to at least one body region, labelling, cropping, and orientating the image to obtain at least one classified, labeled, cropped, and oriented sub-image;
• directing the sub-image to at least one artificial intelligence (AI) processor for processing and obtaining an evaluation result, and comparing the evaluation result to a database library having a plurality of evaluation results and a matched written templates or at least one dataset cluster to obtain at least one cluster result;
• measuring the distance between the cluster result and the evaluation result to obtain at least one cluster diagnosis;
• and
• assembling the cluster diagnosis and the matched written templates to obtain a report and displaying the report to a radiologist thereby identifying and diagnosing the presence of the disease or the condition in the subject.