Abstract: Systems, methods, and devices, for melanoma pathology using one or more neural networks (NNs). The techniques described herein may include receiving molecular data corresponding to a patient biopsy sample; molecular data; encoding molecular output data according to a preselected encoding scheme; receiving image data corresponding to the patient biopsy sample; applying the image data to an image analysis NN; concatenate the encoded molecular data to the image data at an intermediate layer of the image analysis NN; and producing, based on the encoded molecular information and the image information concatenated at the intermediate layer, a prognosis output from the image analysis NN. Many other features and examples are described herein.

Abstract: Systems, methods, and devices for a cancer pathology laboratory information system (LIS) are described herein. Features and solutions described may enhance the efficiency and accuracy with which tissue samples are recorded, processed, and tracked for pathology. For example, a dynamic technician interface may be provided to minimize the quantity of inputs and/or potential errors that may be made by a technician. Also provided are solutions for monitoring, analyzing, and correcting improper or inefficient technician conduct. Many other features and examples are described herein.

Abstract: Systems, methods, and devices for applying neural networks (NNs) to a cancer pathology laboratory information system (LIS) are described herein. Features and solutions described may include receiving technician performance information corresponding to a technician at a technician station; monitoring the technician performance information to detect a breach in sample processing standards; apply the technician performance information and an indication of the breach as input information to one or more neural networks (NNs); dynamically generating a prompt comprising an indication of the breach and the remedy and cause a technician terminal, at the technician station, to generate the prompt; and verifying that the breach has been remedied. Many other features and examples are described herein.

Abstract: Systems, methods, and devices, for melanoma pathology using one or more neural networks (NNs). The techniques described herein may include receiving molecular data corresponding to a patient biopsy sample; molecular data; encoding molecular output data according to a preselected encoding scheme; receiving image data corresponding to the patient biopsy sample; applying the image data to an image analysis NN; concatenate the encoded molecular data to the image data at an intermediate layer of the image analysis NN; and producing, based on the encoded molecular information and the image information concatenated at the intermediate layer, a prognosis output from the image analysis NN. Many other features and examples are described herein.