Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for using machine learning to generate precision predictions of readiness. In some implementations, a database is accessed to obtain status data that indicates activities or attributes of a subject. A set of feature scores is derived from the status data for the subject, the set of feature scores including values indicative of attributes or activities of the subject. The set of feature scores to one or more models that have been configured to predict readiness of subjects to satisfy one or more readiness criteria. The one or models can be models configured using machine learning training. Based on processing performed using the one or more machine learning models and the set of feature scores, a prediction regarding the subject's ability to achieve readiness to satisfy the one or more readiness criteria is generated.

The disclosure relates to methods of signatures which can be used in order to classify patients and predict responsiveness to therapy. In particular, the disclosure relates to RAINFOREST (tReAtment benefit prediction using raNdom FOREST), a new method to discover signatures capable of identifying a subgroup of patients more likely to benefit from a specific treatment as compared to another treatment.

The disclosure relates to methods of signatures which can be used in order to classify patients and predict responsiveness to therapy. In particular, the disclosure relates to RAINFOREST (tReAtment benefit prediction using raNdom FOREST), a new method to discover signatures capable of identifying a subgroup of patients more likely to benefit from a specific treatment as compared to another treatment.

The disclosed embodiments are directed to methods for dynamically adjusting the total daily insulin requirements of a user during pregnancy, based on the gestational week. An initial estimate of the adjusted total daily insulin requirement may be calculated as a multiple of the pre-pregnancy total daily insulin requirement, based on an average scale factor from a population of pregnant women suffering from Type I diabetes mellitus. An automatic drug delivery device may adjust the initial estimate of the total daily insulin requirement based on blood glucose level readings from a continuous glucose monitor during the course of the pregnancy.

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.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for responding to a query. In some implementations, a computer obtains a query. The computer determines a meaning for each term in the query. The computer determines user data for the user that submitted the query. The computer identifies one or more ontologies based on the meanings for at least some of the terms. The computer identifies a knowledge graph based on the identified ontologies and the user data. The computer generates a response to the query by traversing a path of the identified knowledge graph to identify items in the knowledge graph based on the determined meaning for each of the terms. The computer generates path data that represents the path taken by the computer through the identified knowledge graph. The computer provides the generated response and the path data to the client device.

A first examination identification unit identifies examination data including predetermined diagnosis data from among multiple pieces of examination data held in a recorder. A second examination identification unit identifies respective pieces of examination data of multiple examinations performed on a same patient after an examination date included in the examination data identified by the first examination identification unit from among the multiple pieces of examination data held in the recorder. An information acquisition unit acquires, based on multiple pieces of examination data identified by the first examination identification unit and the second examination identification unit, a period from the examination date included in the examination data identified by the first examination identification unit until the complete cure of the patient and the number of examinations performed until the complete cure of the patient. A derivation unit derives an appropriate examination interval and an appropriate number of examinations based on the period and the number of examinations acquired by the information acquisition unit from the plurality of pieces of examination data of the patient.

A medical system of an aspect example includes a data acquiring unit and a data processor. The data acquiring unit is configured to acquire data from an eye fundus of a patient using at least one optical method. The data processor is configured to process the data acquired by the data acquiring unit in order to generate information on the circulatory system of the patient.

Apparatus and associated methods relate to presenting for selection, services comprising at least one bundled set of healthcare services to be performed separately by respective providers, determining a bundle price for the at least one bundled set of healthcare services and in response to receiving payment in an amount of the bundle price, generating a persistent purchase data record with a unique confirmation number that is selectively redeemable by the user to receive each of the healthcare services in the bundled set. The bundle price may be discounted and/or based on the location or time at which at least one service will be performed. The bundle price may also be based on the user's remaining health insurance deductible. A single payment may be disbursed to multiple providers of the bundled set of healthcare services. The received and/or disbursed payment may be in virtual funds.

A method of providing an anti-VLA-4 antibody to a patient.