A method includes causing at least a portion of a knowledge graph representing ontological health related information to be presented on a display of a client device. The method further includes receiving, at an artificial intelligence engine, a medical query, wherein the medical query includes a plurality of strings of characters. The method further includes identifying, in the plurality of strings of characters, indicia comprising a phrase, a predicate, a keyword, a subject, an object, a cardinal, a number, a concept, or some combination thereof. The method further includes comparing the indicia to the knowledge graph to generate an answer responsive to the medical query. The method further includes causing the answer to be presented at the client device.

A handwash monitoring system includes: an imaging device; and a processor. The processor detects a first candidate abnormality existing in a hand of a user from a first image captured by the imaging device before handwashing, and detects a second candidate abnormality existing in the hand of the user from a second image captured by the imaging device after the handwashing. The processor determines a type of an abnormality on the hand of the user based on a difference between a shape of the first candidate abnormality and a shape of the second candidate abnormality wherein the first candidate abnormality and the second candidate abnormality are detected from an identical region.

A system and method for medical audit is provided. Modules each regarding a different patient status are maintained. A chatbot is activated and a status of a patient is received. One of the modules for the patient is selected based on the patient status. Requests for information are provided to the patient based on the selected module and information from the patient is received in response to the requests. The information is checked for compliance with a set of standards selected for the information and the patient is notified that the information does not comply.

A system and method for medical audit is provided. Modules each regarding a different patient status are maintained. A chatbot is activated and a status of a patient is received. One of the modules for the patient is selected based on the patient status. Requests for information are provided to the patient based on the selected module and information from the patient is received in response to the requests. The information is checked for compliance with a set of standards selected for the information and the patient is notified that the information does not comply.

The disclosure provides methods that facilitate disease management by providing for early detection of metabolic changes that differentiate critically ill-COVID-19 patients under mechanical ventilation at the intensive care unit (ICU) who are likely to exhibit faster recovery.

An inventory system configured for detecting and counting potentially retained surgical items within a body of a patient includes a dual detection tag, a signal generator, and an antenna operably coupled to the signal generator. The dual detection tag includes a beacon tag configured to transmit a first return signal at a first frequency when energized and a RFID tag affixed configured to transmit a second return signal at a second frequency when energized. The signal generator is configured to generate an energizing signal for the beacon tag and/or the RFID tag. The antenna configured to receive the first return signal transmitted by at least one of the beacon tag or the second return signal transmitted by the RFID tag.

An inventory system configured for detecting and counting potentially retained surgical items within a body of a patient includes a dual detection tag, a signal generator, and an antenna operably coupled to the signal generator. The dual detection tag includes a beacon tag configured to transmit a first return signal at a first frequency when energized and a RFID tag affixed configured to transmit a second return signal at a second frequency when energized. The signal generator is configured to generate an energizing signal for the beacon tag and/or the RFID tag. The antenna configured to receive the first return signal transmitted by at least one of the beacon tag or the second return signal transmitted by the RFID tag.

A patient care method through artificial intelligence-based monitoring in accordance with one example of the present disclosure comprises steps of: obtaining image information relating a user by a first collecting portion, obtaining speech information relating to the user by a second collecting portion and obtaining biometrics information relating to the user by a third collecting portion (Step 1); representing at least a part of a plurality of information obtained from the first collecting portion, the second collecting portion and the third collecting portion, through a display portion of a user table (Step 2); determining health condition of the user, based on a part of the plurality of information obtained from the first collecting portion, the second collecting portion and the third collecting portion by a server (Step 3); controlling the display portion of the user table to represent a first information automatically generated based on the determined heath condition by the server (Step 4), wherein the first information is converted in real time based on user's feedback on the first information and represents a change in the determined health condition on the display portion.

Methods and systems for classifying and editing insurance claims records are described. In one embodiment, a method, which can be performed by a processor, includes determining that a first prescription drug prescribed to a first patient should be filled by a pharmacy, determining a first guidepost date and a second guidepost date related to the first prescription, determining a third guidepost date associated with a second prescription, comparing the third guidepost date to the first and second guidepost dates to determine whether the third guidepost date occurs after the first guidepost date and before the second guidepost date, and filling and dispensing the first prescription drug as a full prescription supply and the second prescription drug as a full prescription supply on the same dispense date when the third guidepost date occurs after the first guidepost date and before the second guidepost date.

Embodiments of architecture, systems, and methods to develop a learning/evolving system to robotically perform and model one or more activities of a medical procedure where the medical procedure may include diagnosing a patient's medical condition(s), treating medical condition(s), and robotically diagnosing a patient's medical condition(s) and performing one or more medical procedure activities based on the diagnosis without User intervention where the activities may be performed in computer-based environment formed by the learning/evolving system, live, or a combination thereof.