Abstract: Systems and methods for authenticating material samples are provided. Digital images of the samples are processed to extract computer-vision features, which are used to train a classification algorithm along with location and optional time information. The extracted features/information of a test sample are evaluated by the trained classification algorithm to identify the test sample. The results of the evaluation are used to track and locate counterfeits or authentic products.

Abstract: Systems and methods for detecting/identifying novel material samples are provided. A test sample image is processed with a trained transformation function to obtain a transformed matrix. A measure of similarity of the test image based on the transformed matrix is compared to a threshold to determine whether the test sample is novel to a batch of material samples that are provided to train the transformation function.

Abstract: In some examples, a system for detecting inhibition of a biological assay includes a detection device configured to amplify and detect a target nucleic acid. The detection device is configured to receive a sample comprising a matrix and a quantity of the target nucleic acid and to amplify the target nucleic acid within the sample over a nucleic acid amplification cycle. The detection device is configured to capture a data set including measurements of the nucleic acid collected during the amplification cycle. The system further includes a computing device configured to receive the data set and to apply a machine-learning system to the data set to detect inhibited biological assays that tested negative for the target nucleic acid due to matrix inhibition.

Abstract: Systems and methods for authenticating material samples are provided. Digital images of the samples are processed to extract computer-vision features, which are used to train a classification algorithm. The computer-vision features of a test sample are evaluated by the trained classification algorithm to identify the test sample.

Abstract: In some examples, a system for amplifying and quantifying a target organism present in a sample includes a detection device configured to amplify and detect a nucleic acid associated with the target organism. The detection device configured to receive a sample and to amplify nucleic acid in the sample over an amplification cycle. The detection device is configured to capture a data set including measurements of the nucleic acid collected during the amplification cycle. The system further includes a computing device configured to receive the data set and to apply a machine learning system to the data set. The machine learning system is trained to estimate a quantity of the target organism present in the sample based on the measurements in the data set.

Abstract: Aspects of the present disclosure related to a computer system and method for analyzing whether a package has been opened. The system includes a memory and one or more processors communicatively coupled to the memory and can be configured to receive an image corresponding to a wrapped package. The one or more processors can also be configured to generate a set of feature values based on a visual representation of the wrapped package in the image. The one or more processors can also be configured to apply the set of feature values to at least one model that is trained based at least in part on a set of images that include the wrapped package having the status, to determine the status of the wrapped package.

Abstract: Systems and methods for detecting/identifying novel material samples are provided. A test sample image is processed with a trained transformation function to obtain a transformed matrix. A measure of similarity of the test image based on the transformed matrix is compared to a threshold to determine whether the test sample is novel to a batch of material samples that are provided to train the transformation function.

Abstract: In one example, a system includes one or more personal protective equipment (PPE) devices each configured to be worn by a worker, the PPE devices each including one or more sensors that generate activity data indicative of activities of workers operating within one or more work environments. The system also includes a computing device, the computing device configured to: identify, based at least on the activity data, a plurality of clusters of one or more entities, wherein each entity of the entities is associated with one or more of the workers; and output an indication of a difference between performance by a target entity with respect to safety events and performance by the cluster that includes the target entity with respect to safety events.

Abstract: In one example, a system includes one or more personal protective equipment (PPE) devices each configured to be worn by a worker, the PPE devices each including one or more sensors that generate activity data indicative of activities of workers operating within one or more work environments. The system also includes a computing device, the computing device configured to: identify, based at least on the activity data, a plurality of clusters of one or more entities, wherein each entity of the entities is associated with one or more of the workers; and output an indication of a difference between performance by a target entity with respect to safety events and performance by the cluster that includes the target entity with respect to safety events.

Abstract: Systems and methods for authenticating material samples are provided. Digital images of the samples are processed to extract computer-vision features, which are used to train a classification algorithm along with location and optional time information. The extracted features/information of a test sample are evaluated by the trained classification algorithm to identify the test sample. The results of the evaluation are used to track and locate counterfeits or authentic products.

Abstract: Systems and methods for authenticating material samples are provided. Digital images of the samples are processed to extract computer-vision features, which are used to train a classification algorithm. The computer-vision features of a test sample are evaluated by the trained classification algorithm to identify the test sample.

Abstract: In one example, a system includes one or more personal protective equipment (PPE) devices each configured to be worn by a worker, the PPE devices each including one or more sensors that generate activity data indicative of activities of workers operating within one or more work environments. The system also includes a computing device, the computing device configured to: identify, based at least on the activity data, a plurality of clusters of one or more entities, wherein each entity of the entities is associated with one or more of the workers; and output an indication of a difference between performance by a target entity with respect to safety events and performance by the cluster that includes the target entity with respect to safety events.

Abstract: This disclosure provides systems and methods for monitoring respiratory parameters of a person (e.g., a user). In some examples, a system for respiratory monitoring includes a sensor and a computing device. The sensor monitors at least one respiratory related parameter. The computing device is connected to the sensor. The computing device includes a processor. The processor receives a feature vector having a plurality of features, each respective feature associated with a respective respiratory related parameter. The processor also receives from the sensor the at least one respective respiratory related parameter. The processor determines a first breathing state based on the feature vector.

Abstract: Aspects of the present disclosure related to a computer system and method for analyzing whether a package has been opened. The system includes a memory and one or more processors communicatively coupled to the memory and can be configured to receive an image corresponding to a wrapped package. The one or more processors can also be configured to generate a set of feature values based on a visual representation of the wrapped package in the image. The one or more processors can also be configured to apply the set of feature values to at least one model that is trained based at least in part on a set of images that include the wrapped package having the status, to determine the status of the wrapped package.

Abstract: A method of optimizing a query over a database, the method includes obtaining a set of data records from the database, the data records containing structured data and unstructured data documents, extracting the structured and unstructured data from the set of data records, transforming the structured and unstructured data into a vector that is an element of a weighted vector space, receiving a target data record containing structured and unstructured data, generating a target vector for the target data record, executing a similarity algorithm using the target vector and the weighted vector space generated by the collection of database records to provide a reduced number of data records that are most similar to the target data record, and executing a query against the reduced number of data records that are most similar to the target data record.

Abstract: A method of evaluating a plurality of patient protocols associated with a medical context, the method including, with a computer system, accessing a database including medical information for a plurality of patients associated with the medical context items. For each of the patients, the medical information includes an indication that one of the patient protocols is associated with the patient. The method further includes, with the computer system, evaluating each of the patient protocols based on medical information associated with patients within a patient population, the patient population representing a subset of the patients, to estimate an efficacy of each of the patient protocols for the patient population, and identifying the patient population represents a low-efficacy patient population based on the efficacy estimates for the patient population. The method further includes storing, within the database, an indication that the patient population represents the low-efficacy patient population.

Abstract: A computer-implemented method of evaluating a plurality of protocols associated with a medical context includes receiving, with a computer system, an indication of a medical context item corresponding to a medical context, accessing, with the computer system, a digital library including a plurality of protocols associated with the medical context, assigning, with the computer system, predictive outcomes to one or more of plurality of protocols, selecting, with the computer system, one of the plurality of protocols associated with the medical context based upon the assigned predictive outcomes, and storing, with the computer system within a database, an indication the selected protocol is assigned to the medical context item.