Abstract: Methods, systems, and computer-readable media for multi-domain, multi-modal data segmentation, and automatically generating and refining hypotheses. The method receives data from a plurality of data sources; synthesizing the receive data; identifying trigger event data based on the synthesized data; generating an episode based on a segmentation of the synthesized data and trigger event data; and identifying at least one set of observational features associated with the episode based on the synthesized data and a relevancy metric. The method also includes iteratively generating a hypothesis based on the observational features using machine learning, predicting an outcome based on the hypothesis using machine learning, generating an outcome measure, and validating the hypothesis based on the outcome measure.

Abstract: Blockchain-based technologies to facilitate traceability of products through their lifecycle, including design, development, manufacturing, supply chain, and use. The system provides transparent, secure traceability through product lifecycle, drawing insights from collected data and post-market activities. For example, the system could receive tracking data from a plurality of tracking sources along a product's lifecycle and generate one or more blocks in a blockchain to capture the tracking data from the plurality of tracking sources along the product's lifecycle in one or more distributed ledgers.

Abstract: There is provided a radiotherapy system, a data processing method and a storage medium. The radiotherapy system includes a calibration database, a training module and a data processing module. The calibration database can acquire a plurality of the sample data generated in a clinical therapy process. The training module can perform deep learning on the plurality of sample data stored in the calibration database to obtain a therapy algorithm model. The data processing module can process the detection data received in the clinical therapy process according to the therapy algorithm model to generate preliminary therapy data. As the therapy algorithm model is obtained by performing deep learning on a large amount of clinical data, the reliability of the therapy algorithm model is high. Accordingly, the accuracy of the preliminary therapy data generated by the therapy algorithm model is also high.

Abstract: A healthcare worker smart visor. The smart visor comprises a radio transceiver, a non-transitory memory, a camera, a processor communicatively coupled to the radio transceiver, the non-transitory memory, and the camera, an optical visor, a head-up display projector that is communicatively coupled to the processor and that is operable to project an image on an inside surface of the optical visor, a headband retaining the radio transceiver, the non-transitory memory, the camera, the processor, the optical visor, and the head-up display projector, and a smart visor application stored in the non-transitory memory that, when executed by the processor performs two-factor authentication of a healthcare worker, transmits a request for current indications of healthcare equipment via the radio transceiver to the healthcare equipment based on the identity of the healthcare equipment, and presents the current indications on the inside surface of the optical visor via the head-up display.

Abstract: Methods and systems for mobile automation control of disease spread are disclosed. A computer-implemented method includes: determining, by a computing device, a health status of a person; determining, by the computing device, that the person is sick based on the health status; determining, by the computing device, facial and body movements of the person determined to be sick; determining, by the computing device, that the person determined to be sick performed a germ-transmitting activity based on the facial and body movements; and deploying, by the computing device, a cleaning robot to clean based on the determining that the person determined to be sick performed the germ-transmitting activity.

Abstract: A computing system can determine a subset of the users that are to be affected by a predicted event. For each respective user of the subset of users, the system performs a lookup that identifies unique property characteristics of the respective user. Based on the unique property characteristics of the respective user, the system transmits interactive content data to a computing device of the respective user, the interactive content data causing the computing device of the respective user to present interactive mitigation content comprising a customized set of tasks to perform, based on the unique property characteristics of the respective user, to mitigate or prevent loss resulting from the predicted event.

Abstract: A machine learning model is generated for drug efficacy prediction in treatment of genetic disease from a dataset correlating gene expression data for disease-cell samples with drug efficacy values for the samples. Bias weights are stored that correspond to respective genes in the samples. Each bias weight is dependent on predetermined relevance of the respective gene to drug efficacy. The model is generated by processing the dataset via a tree ensemble method wherein decision trees are grown with splits corresponding to respective genes in the samples. The gene for each split is chosen from a respective subset of the genes, and genes are selected for inclusion in this subset with respective probabilities dependent on the corresponding bias weights. The model is stored, and can be applied to gene expression data measured for a patient to obtain a personalized drug efficacy prediction for devising a personalized course of treatment.

Abstract: A system and method for extracting data from an electronic health record to provide provider and patient data similarity scoring includes: encoding a problem list for a plurality of patients with concepts from a common electronic health record ontology. In one aspect, the patients have electronic health records maintained by a plurality of providers. The system and method then may parse the concepts into a plurality of clusters or categories and determining, for each of the providers, a total number of patients that have at least one problem in a cluster or category or determining, for each patient, which of the plurality of clusters or categories correspond to at least one concept encoded in the patient's problem list. The system and method then may calculate for each pair of providers or patients, a distance between the providers or patients.

Abstract: A method for optimizing orthopedic spinal implant survival using preoperative finite element analysis combined with intraoperative stress analysis. Based on clinically relevant data, finite element analysis, and corrected values of spinal parameters, an acceptable long-term stress score is determined for an appropriate implant, which is selected from a set of potential implants, such that the shape of the implant minimizes predicted stress values. From a preoperative medical image set, values of selected spinal alignment parameters are determined; finite element analysis is performed on potential implants to determine stress values; and a selected implant is digitally positioned in the medical image set to create a virtual bone/implant configuration. After the selected implant is inserted and bent to shape, actual stress values are measured intraoperatively.

Abstract: A system includes a processor and a memory including instructions that are executable for causing the processor to perform operations. The operations include accessing a new component value and a set of inner heaps. Each inner heap of the set of inner heaps includes a sorted set of components originating from a plurality of component sources. The operations further include assigning the new component value to a first inner heap of the set of inner heaps. In response to assigning the new component value to the first inner heap, the operations include sorting the first inner heap to identify a maximum or minimum value of the first inner heap. In response to determining that the new component value changes the maximum or minimum value of the first inner heap, the operations include updating an outer heap to include a reference to the new component value of the first inner heap.

Abstract: Systems and methods for treating a patient. The methods comprise: producing, by a radiotherapy system, a fused model for a superficial portion of the patient's skin by combining structural imaging data acquired using high frequency ultrasound and functional imaging data acquired using optical imaging; generating a treatment plan for the patient based on the fused model; storing the treatment plan; detecting, by a processor, an arrival of the patient at a medical facility using first information acquired from a first mobile device coupled to the patient; obtaining the treatment plan using the first information; and causing a state of medical equipment to be transitioned from a first configurable operational state in which a radiotherapy treatment head has a first position to a second configurable operational state in which the radiotherapy treatment head has a second different position, in accordance with the treatment plan.

Abstract: A method and system for managing health care patient record data including identifying and conveying recordation and temporal inconsistencies in health care patient data pertaining to chronic illnesses. An embodiment of the present invention includes identifying a first health care encounter date on which a chronic illness is recorded in a patient's digital health care data and determining if the chronic illness was recorded in the patient's digital health care data for each subsequent health care encounter. Some embodiments also identify the stage of the chronic illness at each encounter to determine if and how the condition of the chronic illness has changed. Some embodiments generate alerts to inform users when a preexisting chronic illness is not subsequently identified and/or if the subsequent diagnosis of the chronic illness indicates that the condition of the chronic illness has changed by some predetermined amount.

Abstract: A method, related system and apparatus are disclosed. The method is implemented by an operative set of processor executable instructions configured for execution by a processor. The method includes the acts of: determining if a monitoring client is connected to a base through a physical connection; establishing a first communications link between the monitoring client and the base through the physical connection; updating, if necessary, the interface program on the monitoring client and the base through the first communications link; establishing a second communications link between the monitoring client and the base using the first communications link; and communicating data from the base to the monitoring client using the second communications link.

Abstract: A system for determining a plurality of biological outcomes using a plurality of dimensions of biological extraction user data and artificial intelligence, the system including a computing device configured to receive, a plurality of dimensions of biological extraction data, generate, a first machine learning process comprising a plurality of biosektch measurements wherein the first machine learning process is trained as a function of training data to output a dimensional history of a user as a function of biological extraction data, output as a function of the plurality of dimensions of biological extraction data and the first machine learning process, the dimensional history of the user; and determine, using a second machine learning process and the dimensional history of the user, at least a biological outcome associated with the user.

Abstract: A device may obtain identification information concerning a clinical trial, and may obtain, based on the identification information, selection information concerning the clinical trial and input information concerning the clinical trial. The device may select at least one machine learning model, of a plurality of machine learning models, based on the selection information, and may process, using the at least one machine learning model, the input information to determine predicted rate of recruitment (RoR) information concerning the clinical trial.

Abstract: A mechanism is provided in a data processing system comprising a processor and a memory, the memory comprising instructions that are executed by the processor to specifically configure the processor to implement a repetitive portion identification and weighting engine. A machine learning model is trained for weighting repetitive portions of patient electronic medical records (EMRs). A repetitive portion identification component applies a plurality of templates to clinical notes of a patient EMR to identify one or more candidate portions that match at least one of the plurality of templates. A content analysis component performs content analysis on the one or more candidate portions to determine whether each given candidate portion is relevant. A weighting component assigns a relative weight to each given candidate portion based on relevance.

Abstract: A system to facilitate the exchange and re-use of industrial waste and byproduct materials that have a reuse possibility is disclosed. The system promotes recycling, reusing, and reclaiming of wastes sustainably to ensure compliance and waste minimization. In one embodiment, the system supports an intelligent service for generating recommendations across an industrial stock exchange. Companies looking to dispose of their wastes or byproducts can access the system to initiate and execute trade with other companies looking for materials or compounds that could be reused in their own manufacturing processes. Both parties will be guided toward their shared goal in order to provide a net-zero impact on the environment and maintain an ecological balance.

Abstract: The disclosure provides a disease classification method and a disease classification device. The disease classification method includes: inputting samples into a first stage model and obtaining a first stage determination result; inputting first samples determined positive by the first stage model into a second stage high specificity model to obtain second samples determined to be positive and third samples determined to be negative and rule in the second samples; inputting fourth samples determined negative by the first stage model into a second stage high sensitivity model to obtain fifth samples determined to be positive and sixth samples determined to be negative and rule out the sixth samples; obtaining a second stage determination result of the second and sixth samples; and inputting the third and fifth samples not ruled in or ruled out into a third stage model and obtaining a third stage determination result of the third and fifth samples.

Abstract: One or more embodiments include obtaining information from a physical payment card. Based on the information from the physical payment card, an output is obtained that includes a valid account number corresponding to the physical payment card. The valid account number is displayed to the cardholder. The physical payment card does not contain a visual indication of the valid account number and thus cannot be used by a malicious entity. One or more embodiments may include a physical payment card. The physical payment card includes a fake account number that cannot be used for executing a transaction based on funds associated with the physical payment card. They physical payment card may also include a key that can be mapped to a valid account number that can be used for executing a transaction based on funds associated with the physical payment card.

Abstract: Methods and systems are provided for generating specific software implementations of neuromodulation-therapy algorithms. A dataset may be received that includes operational specifications that correspond to a plurality of types of neuromodulation-therapy implant devices. A neuromodulation-therapy design interface may provide a representation of the neuromodulation-therapy implant device. A selection if a particular representation of a particular neuromodulation-therapy implant device may be received. Hardware characteristics of the particular neuromodulation-therapy implant device may be used to determine constraints of the implant device. A listing of neuromodulation-therapy parameters that is constraining according to the constraints may be presented. In response to a selection of a parameter, executable software code corresponding to a specific implementation of a neuromodulation-therapy algorithm may be generated.