Abstract: Techniques for performing diagnostic assessments based on digital pathology data are disclosed. In one particular embodiment, the techniques may be realized as a method for performing a diagnostic assessment based on digital pathology data comprising obtaining first digital pathology data comprising intensity information, the first digital pathology data being associated with a plurality of regions of interest in a biological sample; applying first machine learning models to the first digital pathology data, the first machine learning models identifying first regions of interest among the plurality of regions of interest based on the intensity information; applying second machine learning models to the first digital pathology data, the second machine learning models identifying at least one pattern associated with at least one of the first regions of interest; generating a diagnostic assessment based on the first regions of interest and the at least one pattern.

Abstract: Provided herein are agents that bind to soluble beta-amyloid. Also provided are in vivo and in vitro methods for detecting soluble beta-amyloid in a sample that may include brain tissue.

Abstract: Provided herein are agents that bind to soluble beta-amyloid. Also provided are in vivo and in vitro methods for detecting soluble beta-amyloid in a sample that may include brain tissue.

Abstract: An annexin, annexin analogue or phosphatidylserine binding compound (PSC) labeled with an MR, CT, or optical contrast agent. The conjugate is administered into a subject and specifically binds to the surface of apoptotic and necrotic cells. The subject is imaged using conventional MRI, CT and optical imaging techniques and dead and dying tissue is identified. The identification and development of analogues specific for phosphatidylserine for purposes of non-invasive imaging of dead or dying cells.