Abstract: A system provides artificial intelligence health support for people. The system renders specific, targeted treatments for people by using a flow engine and a conversational service to call one or more conversational modules. The treatments for the people may be tracked. The flow engine and/or one or more of the modules may include different instructions to perform for different programs and/or goals that have been configured. The flow engine and/or one or more of the conversational modules may also include instructions to perform when certain features are active (which may be activated when certain programs and/or goals are configured), when data regarding activity for people are received, and so on. Other modules may be dedicated to particular programs and/or goals. Some modules may determine whether or not to perform various instructions repetitiously, and/or may determine to do so when a priority of a previous instruction is below a threshold.

Abstract: A multi-model medical scan analysis system is operable to generate a plurality of training sets from a plurality of medical scans. Each of a set of sub-models is generated by performing a training step on a corresponding one of the plurality of training sets of the plurality of medical scans. A set of abnormality data is generated by applying a subset of a set of inference functions on a new medical scan. The subset of the set of inference functions utilize the subset of the set of sub-models, and each of the set of abnormality data is generated as output of performing one of the subset of the set of inference functions. The multi-model medical scan analysis system is further operable to generate final abnormality data that includes a global probability indicating a probability that any abnormality is present based on the set of abnormality data.

Abstract: Embodiments generally relate to a surgical resource allocation system. Patients seeking a procedure can use the system to identify surgeons and surgical facilities. The patient can then use the system to book the procedure with a selected surgeon at a selected facility. In an example, a patient can indicate a need for a certain procedure. The patient can then provide criteria for a surgeon or facility, such as a desired location, desired time, surgeon rankings, and facility rankings. The system can then identify surgeons and facilities that match the criteria and present them for selection by the patient. The patient can then select the surgeon and facility with which the patient would like the procedure performed. With the surgeon and facility selected, the patient can then choose to book the procedure.

Abstract: Provided is a method of building a cloud-based medical image database for protecting patient information and reading medical image therefrom, the method including: acquiring a medical image of a patient by using a medical apparatus; separating medical information data and patient information data from the medical image; encrypting the patient information data by using a block chain technique; separately transmitting the encrypted patient information data and the medical information data to the cloud-based medical image database, and storing the same in the cloud-based medical image database; decrypting the encrypted patient information data stored in the cloud-based medical image database by using a block chain technique; and performing diagnosis and consulting by reading the medical information data and the patient information data of the medical image according to a big data processing algorithm.

Abstract: Described is a system comprising an input module receiving a first data set indicative of at least one patient condition for each of a plurality of patients obtained during a predetermined time period, a comparison module comparing each of the at least one patient condition to at least one filter criteria, a filter module selecting a patient to include in a second data set if the at least one patient condition of the patient satisfies the at least one filter criteria, a report module generating a report based on the second data set, wherein the report includes at least one patient identifier for each patient in the second data set and at least one descriptor of the at least one patient condition for each patient in the second data set, and a classification module storing at least one classification value for the at least one patient condition.

Abstract: A method of supporting an expert meeting of medical specialists to interpret genetic information, may include: accepting a schedule of the expert meeting; extracting the medical specialists to participate in the expert meeting, the medical specialists stored in association with the accepted schedule of the expert meeting; and transmitting the accepted schedule of the expert meeting to terminal devices of the extracted medical specialists.

Abstract: A system and method for creating a menu for an adapted a medical workflow implemented at a computer coupled to a hospital network is disclosed. The disclosed system and method generates a workflow including a list of predicted medical action options for a medical object based, in part, on a determined operating state or vital state of a patient, creates a menu for displaying the list of predicted medical action options, and communicates the menu for display on a graphic interface. Certain menu selections pertaining to predicted medical action options may be disabled based on state values associated with the medical object.

Abstract: Systems and related methods to estimate, for a liquid dynamic system, flow or resistance based on a model of an object and pressure measurements collected in-situ at said object. Alternatively, pressure flow measurements are collected and pressure or resistance is being estimated.

Abstract: Provided herein are methods for segregating trauma, e.g., blunt trauma, patients into different cohorts based on risk of multiple organ dysfunction syndrome using patient data obtained within a short time window following injury. The methods are useful in providing treatment to trauma patients, and for separating trauma patients into cohorts.

Abstract: In one aspect, a system for automatically processing a medical claim includes a billing automation platform, a navigation device with a global positioning system for collecting patient transport information including a location of a medical encounter, and a computing device for receiving the patient transport information and patient charting information and transmitting the information for use by the billing automation platform. The billing automation platform may access fee schedule(s) based on a location of the medical encounter, automatically populate the medical claim based on the patient charting information, the patient transport information, and the fee schedule(s), and automatically route the medical claim through workflow paths of a claim processing workflow.

Abstract: A method of providing secure access to prescription information includes transmitting a text message including a short URL with a secure token to a device, receiving the secure token, transmitting to the device when the token matches, receiving a refill request; and transmitting a confirmation. A non-transitory computer readable storage medium includes computer-executable instructions that, when executed by a processor, cause a computer to determine a user of a device, provide a status including a short URL with a secure token, receive a short URL access request, validate the request; and provide authorized PHI access. A system includes a processor and a memory storing computer-executable instructions that, when executed by the processor, cause the system to determine a user corresponding to a device, provide a status including a short URL with a secure token, receive a short URL access request, validate the request; and provide authorized PHI access.

Abstract: Upon receipt and verification of a patient's key, a medical questionnaire may be provided to a patient via an electronic device (e.g., computer, mobile phone, etc.). A set of responses to the medical questionnaire may be received from the patient and packaged for storage on a blockchain. The packaged set of responses may then be broadcast to the blockchain.

Abstract: A medical scan header standardization system is operable to determine a plurality of counts for a plurality of entries of at least one of a standard set of fields for headers of a plurality of medical images. A standard set of header entries is determined for at least one of the standard set of fields based on including ones of the entries for the each of the standard set of fields with counts of the plurality of counts that compare favorably to a threshold. One of the standard set of header entries is selected to replace an entry of a field of a header of a medical image. A computer vision model is trained utilizing a training set of images that includes the medical image and the selected one of the standard set of header entries. Inference data for at least one new medical scan is generated based on utilizing the computer vision model.

Abstract: An image of a garment is obtained (101). The garment comprises a marker located on an outside surface of the garment. The marker comprises a code string identifying the garment encoded into a visual symbol. The image is processed to generate a data string representing the visual symbol (102). The data string is used to access activity data associated with a sensor of the garment identified by the code string. The system comprises the garment and one or more electronic devices operable to perform the method.

Abstract: This disclosure provides a technology for developing individual proteins for use in industrial processes that include food production. The technology mines sequence data from protein databases by a process that is done partly in silico. Instead of sampling and testing a vast library of compounds, machine learning and implementation narrows the field of functional candidates by predictive modeling based on known protein structure. Candidate proteins that are selected by this analysis are then produced and screened in a high-throughput manner by recombinant expression and testing to determine whether they have a target function. Multiple cycles of the machine learning, database mining, expression, and testing are done to yield potential ingredients suitable for use in the production of foods, cosmetics, agricultural feed, pharmaceutical excipients, and other industrial products.

Abstract: Synthetic compositions comprising a plant element and at least one fungal endophyte are described. The fungal endophyte is capable of improving plant tolerance to biotic stress as compared to a reference plant element not further comprising the endophyte. Examples of biotic stress include the biotic stress caused by a nematode, an aphid, a fleahopper, a lygus bug, a stink bug, a soy looper, a cabbage looper, or a fungus.

Abstract: The present invention relates to a fusion protein having a targeting sequence, exosporium protein, or exosporium protein fragment that targets the fusion protein to the exosporium of a recombinant Bacillus cereus family member and an enzyme having serine protease activity, wherein the enzyme having serine protease activity is from Bacillus firmus or is a variant of such enzyme. The present invention also provides a recombinant Bacillus cereus family member that expresses such fusion protein and exosporium fragments derived from such recombinant Bacillus cereus family member. Methods of using such recombinant Bacillus cereus family members or exosporium fragments derived therefrom for nematode control are also provided.

Abstract: A model-assisted annotating system is operable to receive a first set of annotation data, corresponding to a broad type of annotation data output. A first training step is performed to train a computer vision model using the first set of annotation data. A second set of annotation data corresponding to the broad type of annotation data output is generated performing an inference function utilizing the computer vision model on medical scans. Additional annotation data further specifies the broad type of annotation data output is received. A second training step is performed to generate an updated computer vision model using set of additional annotation data. A third set of annotation data corresponding to the specified type of annotation data output is generated by performing an updated inference function utilizing the updated computer vision model on medical scans.

Abstract: A pegylated, circularly permuted construct of the CapD enzyme (a gamma glutamyl transferase enzyme acting as a hydrolase specific to poly-?-D-glutamic acid) is used to treat anthrax and other bacterial infections, including but not limited to infection with strains that are resistant to available antibiotics.

Abstract: A method and system identifies interactions of a user with one or more medical devices, determines, based on the one or more interactions and a predetermined set of rules, a compliance score associated with the first user, in response to the compliance score not satisfying a threshold compliance score, and reducing an access level of the user to at least one of the one or more medical devices and generates a training program associated with the at least one medical device and the one or more interactions, and automatically, without user involvement, sends a training package associated with the training program to the user and notifies the user to complete the training program using the training package. The system and method also generates a new shift schedule for clinicians responsive to a first shift schedule not satisfying criteria and the clinicians not satisfying respective performance scores.