Lung screening assessment system

A method for execution by a medical assessment system that includes a processor, the method comprising:

• receiving a first computed tomography (CT) scan that includes a plurality of cross-sectional images;
• generating nodule classification data of the first CT scan by utilizing a computer vision model to identify a first nodule in the plurality of cross-sectional images, wherein the nodule classification data includes an assessment score associated with the first nodule;
• identifying a first subset of a plurality of stored CT scans by applying a similarity function to determine that a set of nodules included in the first subset compare favorably to the first nodule;
• retrieving a set of patient records corresponding to the first subset, wherein each of the set of patient records includes a plurality of record entries and a corresponding plurality of dates;
• identifying a subset of the plurality of dates in the each of the set of patient records that are more recent than a date associated with the one of the first subset corresponding to the each of the set of patient records;
• identifying a subset of the plurality of record entries of the each of the set of patient records that correspond to the subset of the plurality of dates;
• generating longitudinal data corresponding to the set of patient records based on the subset of the plurality of record entries;
• generating a medical assessment report for display on a display device associated with a user of the medical assessment system, wherein the medical assessment report includes the assessment score of the nodule classification data, data from at least one patient record in the set of patient records and the longitudinal data;
• and
• selecting at least one cross sectional image from each CT scan of the first subset of CT scans for display on the display device in conjunction with the medical assessment report.

A medical assessment system comprising:

• means for receiving a first computed tomography (CT) scan that includes a plurality of cross-sectional images;
• means for generating nodule classification data of the first CT scan by utilizing a computer vision model to identify a first nodule in the plurality of cross-sectional images, wherein the nodule classification data includes an assessment score associated with the first nodule;
• means for identifying a first subset of a plurality of stored CT scans by applying a similarity function to determine that a set of nodules included in the first subset compare favorably to the first nodule;
• means for retrieving a set of patient records corresponding to the first subset, wherein each of the set of patient records includes a plurality of record entries and a corresponding plurality of dates;
• means for identifying a subset of the plurality of dates in the each of the set of patient records that are more recent than a date associated with the one of the first subset corresponding to the each of the set of patient records;
• means for identifying a subset of the plurality of record entries of the each of the set of patient records that correspond to the subset of the plurality of dates;
• means for generating longitudinal data corresponding to the set of patient records based on the subset of the plurality of record entries;
• means for generating a medical assessment report for display on a display device associated with a user of the medical assessment system, wherein the medical assessment report includes the assessment score of the nodule classification data, data from at least one patient record in the set of patient records and the longitudinal data;
• and
• means for selecting at least one cross sectional image from each CT scan of the first subset of CT scans for display on the display device in conjunction with the medical assessment report.