Abstract: Systems and methods for tracking an evolution of a disease in a colon of a patient over time are configured for operations including receiving video data representing a colon of a patient; segmenting the video data into segments representing portions of a colon of the patient; extracting, from the video data based on the segmenting, a set of features representing locations in the colon of the patient; and registering the feature vector as representing the colon of the patient for tracking the evolution of the disease in the colon of the patient. The system can be configured to predict disease progression predict drug dosage for patients.

Abstract: Generating a structured medical record from endoscopy data includes obtaining image data including endoscopic images representing portions of a gastrointestinal tract (GI) of a patient; determining features to extract from the image data, the features each representing a physical parameter of the GI tract; extracting the features from the image data; generating anatomical location data specifying a location within the GI tract of a portion of the GI tract represented in the image data; associating the anatomical location data with images that represent the portion of the GI tract; storing, in a node of a data store, data entries including the anatomical location data and the associated one or more images. The data store is configured to receive structured queries for the data entries in the data store and provide the data entries including the transformed features in response to receiving the structured queries.

Abstract: This specification describes systems and methods for performing endoscopy, obtaining medical images for inflammatory bowel disease (IBD) and scoring severity of IBD in patients. The methods and systems are configured for using machine learning to determine measurements of various characteristics related to IBD. The methods and systems may also obtain and incorporate electronic health data of patients along with endoscopic data to use for scoring purposes.

Abstract: One or more machine learning techniques can be used to identify locations of potential malignancies within images (e.g., video images) captured during a medical procedure, such as an endoscopic procedure. The images can be displayed, in real-time, on a display unit. The images can be displayed with a graphical overlay that isolates the identified locations of potential malignancies.

Abstract: This specification describes systems and methods for obtaining various patient related data for inflammatory bowel disease (IBD). The methods and systems are configured for using machine learning to determine measurements of various characteristics and provide analysis related to IBD. The methods and systems may also obtain and incorporate electronic health data as well as other relevant data of patients along with endoscopic data to use for prediction IDB progression and recommending treatment.

Abstract: One or more machine learning techniques can be used to identify locations of potential malignancies within images (e.g., video images) captured during a medical procedure, such as an endoscopic procedure. The images can be displayed, in real-time, on a display unit. The images can be displayed with a graphical overlay that isolates the identified locations of potential malignancies.