A system and method are presented in which known genetic attributes associated with a condition are used to seed the determination of additional attributes which are associated with the condition. Based on the learning, the additional attributes (genetic, behavioral, or both) provide for an increased correlation between the combined attributes and the condition. For behavioral attributes, a measure of the impact of the behavioral attribute on the risk of the condition can be transmitted to another device or system.

A system and method are presented in which known genetic attributes associated with a condition are used to seed the determination of additional attributes which are associated with the condition. Based on the learning, the additional attributes (genetic, behavioral, or both) provide for an increased correlation between the combined attributes and the condition. For behavioral attributes, a measure of the impact of the behavioral attribute on the risk of the condition can be transmitted to another device or system.

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.

For machine training and application of a trained complex-valued machine learning model, an activation function of the machine learning model, such as a neural network, includes a learnable parameter that is complex or defined in a complex domain with two dimensions, such as real and imaginary or magnitude and phase dimensions. The complex learnable parameter is trained for any of various applications, such as MR fingerprinting, other medical imaging, or non-medical uses.

For machine training and application of a trained complex-valued machine learning model, an activation function of the machine learning model, such as a neural network, includes a learnable parameter that is complex or defined in a complex domain with two dimensions, such as real and imaginary or magnitude and phase dimensions. The complex learnable parameter is trained for any of various applications, such as MR fingerprinting, other medical imaging, or non-medical uses.

Provided are a brain stimulation system, method, apparatus and storage medium based on artificial intelligence. The system includes: a plurality of brain stimulation terminals and a cloud platform. The cloud platform is configured to, with artificial intelligence algorithm especially machine learning and deep learning, generate multi-dimensional psychological big data using physiological data and psychological state evaluation parameters gotten from the plurality of brain stimulation terminals and established models of algorithm for disease diagnosis. The brain stimulation terminal is configured to analyze the physiological data and psychological state evaluation parameters of a target subject, measure a mental state of the target subject, obtain brain stimulation parameters required for the target subject according to the mental state, and generate corresponding non-invasive brain stimulation for the target subject according to the brain stimulation parameters based on the multi-dimensional big data through the artificial intelligence algorithm.

A medical system comprises processing circuitry configured to: receive a first trained model, wherein the trained model has been trained using a first data set acquired in a first cohort; receive a second data set acquired in a second cohort; input data included in the second data set and data representative of the first trained model into a second trained model; and receive from the second trained model an affinity-relating value which represents an affinity between the data included in the second data set and the first trained model.

The application relates to providing medical information in response to a query, in particular, although not exclusively, to a method of querying a medical database using voice recognition. According to an embodiment, there is provided a medical query answering apparatus that is configured to convert detected audio signals into a natural language data stream; determine from the natural language data stream whether a voice command for information relating to a medical device or a medicament has been issued by a user; in response to a positive determination, convert at least part of the natural language data stream into a query for querying a medical database; supply the query to the medical database and receive a response therefrom; and provide an audio output based at least in part on the response from the medical database.

The application relates to providing medical information in response to a query, in particular, although not exclusively, to a method of querying a medical database using voice recognition. According to an embodiment, there is provided a medical query answering apparatus that is configured to convert detected audio signals into a natural language data stream; determine from the natural language data stream whether a voice command for information relating to a medical device or a medicament has been issued by a user; in response to a positive determination, convert at least part of the natural language data stream into a query for querying a medical database; supply the query to the medical database and receive a response therefrom; and provide an audio output based at least in part on the response from the medical database.

An approach for improving determining a significant slice associated with a tumor from a volume of medical images is disclosed. The approach is based on the annotation of tumor range and the slice index in which the tumor appears to have the largest area. The approach infer a tumor growth classifier on sliding window of the volume slices and creates a discrete integral function out of the classifier predictions. The approach applies post processing on the discrete integral function which can include a smoothing function and a bias correction. The approach selects the slice index of maximum value from the post processing step.