Abstract: The present disclosure describes a deep learning algorithm with the ability to provide a high-performance classifier to predict either the presence of geographic atrophy (GA), or the likelihood of progression from intermediate age-related macular degeneration to GA. The system can also be used for broader applications outside of eye disease.

Abstract: A system includes a camera configured to generate image data and a computing device in electronic communication with the camera. The computing device includes at least one processor and is configured to receive, from the camera, one or more images representative of a location. The computing device is further configured to apply a trained classifier to the one or more images to classify the location into one of at least two risk categories, wherein the classification is based on a likelihood of a subject performing a target behavior based on presence of the subject in the location. The computing device is additionally configured to issue a risk alert responsive to the trained classifier classifying the location into a high-risk category.

Abstract: A federated machine-learning system includes a global server and client devices. The server receives updates of weight factor dictionaries and factor strengths vectors from the clients, and generates a globally updated weight factor dictionary and a globally updated factor strengths vector. A client device selects a group of parameters from a global group of parameters, and trains a model using a dataset of the client device and the group of selected parameters. The client device sends to the server a client-updated weight factor dictionary and a client-updated factor strengths vector. The client device receives the globally updated weight factor dictionary and the globally updated factor strengths vector, and retrains the model using the dataset of the client device, the group of parameters selected by the client device, and the globally updated weight factor dictionary and the globally updated factor strengths vector.

Abstract: A system includes a camera configured to generate image data and a computing device in electronic communication with the camera. The computing device includes at least one processor and is configured to receive, from the camera, one or more images representative of a location. The computing device is further configured to apply a trained classifier to the one or more images to classify the location into one of at least two risk categories, wherein the classification is based on a likelihood of a subject performing a target behavior based on presence of the subject in the location. The computing device is additionally configured to issue a risk alert responsive to the trained classifier classifying the location into a high-risk category.

Abstract: Transmission microscopy imaging systems include a mask and/or other modulator situated to encode image beams, e.g., by deflecting the image beam with respect to the mask and/or sensor. The beam is modulated/masked either before or after transmission through a sample to induce a spatially and/or temporally encoded signal by modifying any of the beam/image components including the phase/coherence, intensity, or position of the beam at the sensor. For example, a mask can be placed/translated through the beam so that several masked beams are received by a sensor during a single sensor integration time. Images associated with multiple mask displacements are then used to reconstruct a video sequence using a compressive sensing method. Another example of masked modulation involves a mechanism for phase-retrieval, whereby the beam is modulated by a set of different masks in the image plane and each masked image is recorded in the diffraction plane.

Abstract: Transmission microscopy imaging systems include a mask and/or other modulator situated to encode image beams, e.g., by deflecting the image beam with respect to the mask and/or sensor. The beam is modulated/masked either before or after transmission through a sample to induce a spatially and/or temporally encoded signal by modifying any of the beam/image components including the phase/coherence, intensity, or position of the beam at the sensor. For example, a mask can be placed/translated through the beam so that several masked beams are received by a sensor during a single sensor integration time. Images associated with multiple mask displacements are then used to reconstruct a video sequence using a compressive sensing method. Another example of masked modulation involves a mechanism for phase-retrieval, whereby the beam is modulated by a set of different masks in the image plane and each masked image is recorded in the diffraction plane.

Abstract: Methods of identifying infectious disease infection prior to presentation of symptoms, assays for identifying genomic markers of infectious disease, and methods for diagnosing the underlying etiology of infectious disease.

Abstract: A computerized method for transforming a signal representative of image information, the signal being a sparse signal, includes obtaining the signal. The method further includes using the signal to learn a dictionary of basis functions that represent at least part of the signal. The method further includes using the learned dictionary of basis functions to transform the signal.

Abstract: Methods of identifying infectious disease infection prior to presentation of symptoms, assays for identifying genomic markers of infectious disease, and methods for diagnosing the underlying etiology of infectious disease.

Abstract: The present invention is directed to methods for diagnosis of sepsis and high risk of sepsis death. Such methods are directed to subjects presenting to healthcare facilities with symptoms for sepsis. Clinico-metabolomic classifiers are tested and compared in the methods of the present invention.

Abstract: A visitor control and tracking system for a venue having various access points and multiple destination points includes a monitoring system that tracks location and movement of visitors to the venue. Prior to entering the venue, visitors first interact with one of a plurality of screening centers which performs a security scan. A controller operatively connected to the plurality of screening centers determines a visitor associated metric for each of the plurality of destination points. Once the controller determines the visitor associated metric, information is provided to the visitors that will help guide them about the venue. The information can be provided on a display provided on each of the plurality of screening centers and/or on displays provided about the venue.

Abstract: A method of quantifying similarities between sequential data streams typically includes providing a pair of sequential data streams, designing a Hidden Markov Model (HMM) of at least a portion of each stream; and computing a quantitative measure of similarity between the streams using the HMMs. For a plurality of sequential data streams, a matrix of quantitative measures of similarity may be created. A spectral analysis may be performed on the matrix of quantitative measure of similarity matrix to define a multi-dimensional diffusion space, and the plurality of sequential data streams may be graphically represented and/or sorted according to the similarities therebetween. In addition, semi-supervised and active learning algorithms may be utilized to learn a user's preferences for data streams and recommend additional data streams that are similar to those preferred by the user. Multi-task learning algorithms may also be applied.

Abstract: The Analyst Cueing method addresses the issues of locating desired targets of interest from among very large datasets in a timely and efficient manner. The combination of computer aided methods for classifying targets and cueing a prioritized list for an analyst produces a robust system for generalized human-guided data mining. Incorporating analyst feedback adaptively trains the computerized portion of the system in the identification and labeling of targets and regions of interest. This system dramatically improves analyst efficiency and effectiveness in processing data captured from a wide range of deployed sensor types.

Abstract: The identification and tracking of objects from captured sensor data relies upon statistical modeling methods to sift through large data sets and identify items of interest to users of the system. Statistical modeling methods such as Hidden Markov Models in combination with particle analysis and Bayesian statistical analysis produce items of interest, identify them as objects, and present them to users of the system for identification feedback. The integration of a training component based upon the relative cost of sampling sensors for additional parameters, provides a system that can formulate and present policy decisions on what objects should be tracked, leading to an improvement in continuous data collection and tracking of identified objects within the sensor data set.

Abstract: A visitor control and tracking system for a venue having various access points and multiple destination points includes a monitoring system that tracks location and movement of visitors to the venue. Prior to entering the venue, visitors first interact with one of a plurality of screening centers which performs a security scan. A controller operatively connected to the plurality of screening centers determines a visitor associated metric for each of the plurality of destination points. Once the controller determines the visitor associated metric, information is provided to the visitors that will help guide them about the venue. The information can be provided on a display provided on each of the plurality of screening centers and/or on displays provided about the venue.

Abstract: The present invention provides multidimensional stacked photonic band gap crystal structures improving the performance of current planar monolithic antennas and RF filters by forbidding radiation from coupling into the substrate thereby significantly enhancing radiation efficiency and bandwidth. This invention comprises a number of sub-crystals with each having at least two lattices disposed within a host material, each lattice having a plurality of dielectric pieces arranged and spaced from each other in a predetermined manner, the sub-crystals being stacked in a crystal structure to provide a photonic band gap forbidding electromagnetic radiation propagating over a specially designed frequency band gap, or stopband. Both two dimensional and multidimensional crystals are disclosed.