Systems and methods for point-of-care assessment based on pathology image analysis

A computer-implemented method, comprising, receiving, by a computing device, data defining a set of nuclear morphology features that correlate with chromosomal instability (CIN) scores;

• receiving, by the computing device, image data representing an image of cancerous bodily tissue;
• determining, using the image data, an instance of the set of nuclear morphology features, the instance representing an extent of chromosomal instability inside a cell nucleus within the cancerous bodily tissue;
• determining, using the instance, a metric indicative of a stage or a prognosis;
• and
• causing a device to present the metric.

A computer-implemented method for pathology image classification, the method comprising:

• receiving an image of a cancerous tissue sample for a patient;
• generating a feature vector within an area on the image, wherein the feature vector includes multiple values defining respective targeted histopathologic features of neuroendocrine differentiation;
• determining a metric for the area of cancerous tissue sample on the image by processing the feature vector through a model trained to distinguish tiles of non-metastatic (M0) adenocarcinoma from tiles of small cell carcinoma (SC), and wherein the metric represents an amount of neuroendocrine differentiation present in the area;
• and
• providing the metric for further processing or to a user interface of a computer device.