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.

An external defibrillator system includes one or more compression sensors; one or more physiological sensors; and at least one processor. The at least one processor is configured to: receive and process chest compression signals and physiological signals from the sensors, determine values for chest compression depth and/or chest compression rate based on the received chest compression signals, determine a trend of at least one physiological parameter over a period comprising multiple chest compressions based on the received physiological signals, adjust a target chest compression depth and/or target chest compression rate based on the determined trend of the at least one physiological parameter, compare the determined values for chest compression depth and/or chest compression rate to the adjusted target compression depth and/or the adjusted target compression rate, and provide feedback about the quality of chest compressions performed on the patient.

A differential diagnosis apparatus is described, which is adapted for medical applications in order to determine an optimal sequence of diagnostic tests for identifying a pathology by adopting diagnostic appropriateness criteria, comprising: a first updatable database containing patients' data; a second relational database containing identification data of pathologies, symptoms, clinical signs, identification data of diagnostic tests, and data relating to the appropriateness parameters of said diagnostic tests for defining a list of diagnostic hypotheses (pathologies); means adapted to determine said optimal sequence of diagnostic tests for identifying a pathology, said means comprising an inferential computation engine, which determine for each diagnostic hypothesis (pathology), based on data contained in said first and second databases, said optimal sequence of diagnostic tests with associated indices of appropriateness and probability that a patient is suffering from that pathology.

The present disclosure relates to a method and device for processing human body characteristic data. The method includes: receiving a set of human body characteristic information transmitted by a terminal; and according to requirements of an application to be run, extracting, from the set of human body characteristic information, human body characteristic data corresponding to the application to be run, and performing data reconstruction process on the extracted human body characteristic data.

In an embodiment, a method for estimating a composition of food includes: receiving a first three-dimensional (3D) image; identifying food in the first 3D image; determining a volume of the identified food based on the first 3D image; and estimating a composition of the identified food using a millimeter-wave radar.

A system for generating an immune protocol for identifying and reversing immune disease is presented. The system comprising a computing device configured to receive at least an immune biomarker from a graphical user interface, determine a current immunological state of the user including an immune dysfunction as a function of the immune biomarker and an immune profile, assign an immune category to the immune profile as a function of the current immunological state, identify an effect on the immune profile for each nutritional element of a plurality of nutritional elements, determine at least a nutritional element that contributes to the immune category as a function of an immune machine-learning model and the nutritional input, identify a plurality of protocol elements, wherein each protocol element contains at least a nutrient amount intended to address the immunological dysfunction, and generate an immune protocol as a function of the plurality of protocol elements.

A computerized method includes obtaining a set of entities. The method also includes, for each entity, obtaining data specific to the entity, generating a feature vector based on the data, and processing the feature vector to generate an entity fall likelihood that indicates a likelihood that the entity will experience a fall based on the feature vector. The method further includes determining a subset of entities having entity fall likelihoods that satisfy a threshold. For each entity in the subset, the method includes determining impact scores for parameters of the feature vector associated with the entity and generating a feature list based on the determined impact scores. Each impact score is indicative of an effect of the parameter on the entity fall likelihood for the entity. The feature list is specific to the entity and includes a parameter having the highest impact score.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

Method of predicting a response of a subject to food is disclosed. The method comprises: selecting a food to which a response of the subject is unknown; accessing a first database having data describing the subject but not a response of the subject to the selected food; accessing a second database having data pertaining to responses of other subjects to foods, the responses of the other subjects including responses of at least one other subject to the selected food or a food similar to said selected food; and analyzing the databases based on the selected food to estimate the response of the subject to the selected food.