Abstract: Systems and methods are provided for managing patient data. The system integrates medical data from multiple sources to a unified patient database. Structured and unstructured medical data is obtained, enriched (e.g., by designating data field types, standardizing data types or terminology, and the like), and stored to the unified patient database. The data retrieved from the disparate sources is stored to data elements in the unified patient database in a network of connected objects including data about tumor masses, treatments, reports, medical history, and diagnoses. The data in the unified patient database is used to display patient data in user-friendly interface views, including a patient journey view that displays patient data in a chronological fashion organized by data types. The different interface views can be traversed to display patient data originating from disparate sources with ease, to improve the clinical decision making process.

Abstract: Methods and systems for performing a clinical prediction are provided. In one example, the method comprises: receiving first molecular data of a patient, the first molecular data including at least gene expressions of the patient; receiving first biopsy image data of the patient; processing, using a machine learning model, the first molecular data and the first biopsy image data to perform a clinical prediction of the patient's response to a treatment, wherein the machine learning model is generated or updated based on second molecular data including at least gene expressions and second biopsy image data of a plurality of patients; and generating an output of the clinical prediction.

Abstract: Methods and systems for performing a clinical prediction are provided. In one example, the method comprises: receiving first molecular data of a patient, the first molecular data including at least gene expressions of the patient; receiving first biopsy image data of the patient; processing, using a machine learning model, the first molecular data and the first biopsy image data to perform a clinical prediction of the patient's response to a treatment, wherein the machine learning model is generated or updated based on second molecular data including at least gene expressions and second biopsy image data of a plurality of patients; and generating an output of the clinical prediction.

Abstract: In one example, a method being performed by a computer system comprises: receiving an image file containing a pathology report; performing an image recognition operation on the image file to extract input text strings; detecting, using a natural language processing (NLP) model, entities from the input text strings, each entity including a label and a value; extracting, using the NLP model, the values of the entities from the input text strings; converting, based on a mapping table that maps entities and values to pre-determined terminologies, the values of at least some of the entities to the corresponding pre-determined terminologies; and generating a post-processed pathology report including the entities detected from the input text strings and the corresponding pre-determined terminologies.

Abstract: Methods and systems for providing an interactive guideline are provided. In one example, a method comprises: receiving, from a database, data of a directed graph representing a medical guideline, the medical guideline including a decision tree including a plurality of clinical decisions and preconditions leading to at least some of the clinical decisions, the directed graph including a plurality of nodes representing the clinical decisions and the preconditions and edges connecting the plurality of nodes to represent dependency relationships among the clinical decisions and the preconditions; providing, via a navigation interface, a graphical representation of at least part of the directed graph; receiving, via the navigation interface, a selection of a node of the directed graph from the graphical representation; and based on the selection of the node, updating the graphical representation of the at least part of the directed graph to provide a navigation result of the medical guideline.

Abstract: Methods and systems for performing a clinical prediction are provided. In one example, the method comprises: receiving first molecular data of a patient, the first molecular data including at least gene expressions of the patient; receiving first biopsy image data of the patient; processing, using a machine learning model, the first molecular data and the first biopsy image data to perform a clinical prediction of the patient's response to a treatment, wherein the machine learning model is generated or updated based on second molecular data including at least gene expressions and second biopsy image data of a plurality of patients; and generating an output of the clinical prediction.