A method for autonomously generating a care plan personalized for a patient is disclosed. The method includes receiving a selection of a type of the care plan to implement for the patient, generating the care plan based on the type selected, wherein the care plan includes an action instruction based on a patient graph of the patient and a knowledge graph including ontological medical data, receiving patient data that indicates health related information associated with the patient, modifying the care plan to generate a modified care plan in real-time or near real-time based on the patient data, and causing the modified care plan to be presented on a computing device of a medical personnel.

A system for data process comprises an operating platform for storing and reading a data unit. A data processing module signally connected to the operating platform. The data unit is structured or unstructured. The data processing module labeling and processing the data unit, and generating a visualization diagram. The system for data process includes a graphical user interface, which can achieve one of the purposes of this present disclosure of improving the data visualization of structured data and unstructured data.

The present disclosure provides methods, systems, and non-transitory computer-readable media for assessment of disease treatment or progression on a lesion-by-lesion level. The systems and methods are based on measurements of a variety of features including total number of lesions, total number and proportion of lesions regressing or progressing, changes in dimensions of a lesion over time, and uptake values of a molecular imaging agent.

A system and method for assessing disease progression receives digital health data about patients over a network from a plurality of diagnostic instruments, IoT devices, analytical software, systems, and electronic health records. Electronic Patient Reported Outcome (PRO) questionnaires are created by clinicians and periodically administered to patients on a remote computing device. The PROs and other digital health data are processed, analyzed, and scored in real time. Digital reports including the scores and other health metrics are instantaneously generated providing valuable hidden insights into disease progression and treatment efficacies in real-time. A clinical advisor generates an interactive dashboard comprising comprehensive information about patients and enables doctors to validate their clinical decisions and discover new treatment protocol idea. Reports useful for other industries may also be generated, such as for pharmaceutical companies, insurance companies, medical researchers, and regulatory agencies.

A system and method for determining a health outcome, comprising: receiving first and second images or videos of a wound of a patient; comparing the images or videos to detect a characteristic of the wound, the characteristic including an identification of a change in the wound; receiving at least one non-image or non-video data input that includes data about the patient; executing a machine learning algorithm comprising a dataset of images or videos to analyze the identified change in the wound and to correlate at least one first image or video and at least one second image or video with the at least one non-image or non-video data input and to train the machine learning algorithm with the identification of a change in the wound; and generating a medical outcome prediction regarding a status and recovery of the patient in response to correlating the at least one additional input with the first and second images or videos.

Systems, methods and computer-readable media are provided for facilitating clinical decision support and managing patient population health by health-related entities including caregivers, health care administrators, insurance providers, and patients. Embodiments of the invention provide decision support services including providing timely contextual patient information including condition risks, risk factors and relevant clinical information that are dynamically updatable; imputing missing patient information; dynamically generating assessments for obtaining additional patient information based on context; data-mining and information discovery services including discovering new knowledge; identifying or evaluating treatments or sequences of patient care actions and behaviors, and providing recommendations based on this; intelligent, adaptive decision support services including identifying critical junctures in patient care processes, such as points in time that warrant close attention by caregivers; near-real time querying across diverse health records data sources, which may use diverse clinical nomenclatures and ontologies; improved natural language processing services; and other decision support services.

Among other things, methods, systems and computer program products for providing visual indication of documentation and coding of medical procedures may include providing a choice of medical codes associated with a medical procedure. A user selection of one of the medical codes is detected. Based on the detection, a visual indication of the user selection is generated on one or more anatomical diagrams.

Among other things, methods, systems and computer program products for providing visual indication of documentation and coding of medical procedures may include providing a choice of medical codes associated with a medical procedure. A user selection of one of the medical codes is detected. Based on the detection, a visual indication of the user selection is generated on one or more anatomical diagrams.

Methods, devices, and systems (for outputting a case summary) receive an electronic medical record (EMR) (and generally electronic records) for the medical patient, extract medical data from the EMR, provide a list of medical problems relevant to the EMR, identifying relations between the medical problems and the medical data using a question-answering (QA) system, and output the clinical summary for the EMR. The clinical summary comprises the list of medical problems, the medical data, and the relations.

Methods, devices, and systems (for outputting a case summary) receive an electronic medical record (EMR) (and generally electronic records) for the medical patient, extract medical data from the EMR, provide a list of medical problems relevant to the EMR, identifying relations between the medical problems and the medical data using a question-answering (QA) system, and output the clinical summary for the EMR. The clinical summary comprises the list of medical problems, the medical data, and the relations.