A method, comprising: magnifying a pathology sample with a microscope to form magnified pathology images; recording the magnified pathology images with a digital camera optically coupled to the microscope; comparing the magnified pathology images to reference pathology images included in a pathology database to identify one or more regions of interest in the magnified pathology images, wherein a machine learning algorithm is used to identify the one or more regions of interest, and wherein the machine learning algorithm is trained to identify the one or more regions of interest using the reference pathology images in the pathology database; and alerting a user of the microscope to the one or more regions of interest in the magnified pathology images, and further comprising: identifying areas of the pathology sample that are deemed to be insufficiently reviewed by the user; and informing the user of one or more regions of potential interest in the areas that are deemed to be insufficiently reviewed by the user, wherein the machine learning algorithm is trained to identify the areas of the pathology sample that are deemed to be insufficiently reviewed by the user by tracking if an area was in the user's field of view for a threshold amount of time, and wherein the areas that are deemed to be insufficiently reviewed are further determined by employing location on the pathology sample and level of magnification of the microscope. magnifying a pathology sample with a microscope to form magnified pathology images; recording the magnified pathology images with a digital camera optically coupled to the microscope; comparing the magnified pathology images to reference pathology images included in a pathology database to identify one or more regions of interest in the magnified pathology images, wherein a machine learning algorithm is used to identify the one or more regions of interest, and wherein the machine learning algorithm is trained to identify the one or more regions of interest using the reference pathology images in the pathology database; and alerting a user of the microscope to the one or more regions of interest in the magnified pathology images, and further comprising: identifying areas of the pathology sample that are deemed to be insufficiently reviewed by the user; and informing the user of one or more regions of potential interest in the areas that are deemed to be insufficiently reviewed by the user, wherein the machine learning algorithm is trained to identify the areas of the pathology sample that are deemed to be insufficiently reviewed by the user by tracking if an area was in the user's field of view for a threshold amount of time, and wherein the areas that are deemed to be insufficiently reviewed are further determined by employing location on the pathology sample and level of magnification of the microscope. identifying areas of the pathology sample that are deemed to be insufficiently reviewed by the user; and informing the user of one or more regions of potential interest in the areas that are deemed to be insufficiently reviewed by the user, wherein the machine learning algorithm is trained to identify the areas of the pathology sample that are deemed to be insufficiently reviewed by the user by tracking if an area was in the user's field of view for a threshold amount of time, and wherein the areas that are deemed to be insufficiently reviewed are further determined by employing location on the pathology sample and level of magnification of the microscope. <EOS>