Abstract: Methods and systems are directed to training an artificial intelligence engine. One system includes an electronic processor configured obtain a set of reports corresponding to a set of medical images, determine a label for a finding of interest, and identify one or more ambiguous reports in the set of repots. Ambiguous reports do not include a positive label or a negative label for the finding of interest. The electronic processor is also configured to generate an annotation for each of the one or more ambiguous reports in the set of reports, and train the artificial intelligence engine using a training set including the annotation for each of the one or more ambiguous reports and non-ambiguous reports in the set of reports. A result of the training is generation of a classification model for the label for the finding of interest.

Abstract: An estimation apparatus, a learning apparatus, an estimation method, and a learning method, and a program capable of accurate body tracking without attaching many trackers to a user are provided. A feature extraction section (68) outputs feature data indicating a feature of a time-series transition until a latest timing in response to an input of input data that contains region data indicating a position, a posture, or a motion about a region of a body at the latest timing and feature data indicating the feature of the time-series transition previously output from the feature extraction section (68) at a timing preceding the latest timing. An estimation section (72) estimates a position, a posture, or a motion of another region of a body closer to a center of the body than the region at the latest timing on the basis of the feature data indicating the feature of the time-series transition until the latest timing.

Abstract: An emergency medical treatment system is provided that can be used in connection with providing prehospital medical treatment to a patient. The system includes a patient data display device programmed to receive and display data associated with the patient; an environmental assessment device configured to capture visual, aural, or other ambient environmental data associated with an emergency treatment site associated with the patient; a patient monitoring device configured to be positioned on the patient and having multiple sensors programmed to collect physiological data or vitals data associated with the patient; and a patient data processing device configured with a speech-to-text module. Rules-based or machine learning based algorithm modules can be provided for generating alerts or making treatment option recommendations in connection with the patient data collected and displayed on the patient display device.

Abstract: The present teachings generally include techniques for characterizing the health of an animal (e.g., gastrointestinal health) using image analysis (e.g., of a sample of an exudate such as mucus) as a complement, alternative, or a replacement to traditional laboratory analyses of biological specimens. The present teachings may further include techniques for personalizing a health and wellness plan (including, but not limited to, a dietary supplement such as a customized formula based on a health assessment), where such a plan may be based on one or more of the health characterization techniques described herein. The present teachings may also or instead include techniques or plans for continuous care for an animal, e.g., by executing health characterization and heath planning techniques in a cyclical fashion. A personalized supplement system (e.g., using a personalized supplement, personalized dosing device, and personalized packaging) may also or instead be created using the present teachings.

Abstract: The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

Abstract: A method and system for generating a classifier to classify facial images for cognitive disorder in humans. The system comprises receiving a labeled dataset including set of facial images, wherein each of the facial image is labeled depending on whether it represents a cognitive disorder condition; extracting, from each facial image in the set of facial images, at least one learning facial feature indicative of a cognitive disorder; and feeding the extracted facial features into a to produce a machine learning trained model to generate a classifier, wherein the classifier is generated and ready when the trained model includes enough facial features processed by a machine learning model.

Abstract: In some embodiments, protein biomarker concentration information for a subject is obtained, and is used to determine one or more skin trends likely to be experienced by the subject. Skincare product recommendations are generated based on the protein biomarker concentration information. Feedback on the recommended skincare products may be received, and may be used to improve future recommendations for skincare products for the subject or for other subjects.

Abstract: The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

Abstract: Techniques for automatically attaching optical character recognition data to images are provided. The techniques include receiving an image file containing an image and performing optical character recognition on the image to generate text output. The techniques then continue by identifying a particular text item from within the generated text output and determining that the particular text item is a value for particular corresponding key. Then metadata that indicates that the particular text item is a value for the particular key is stored in the image file.

Abstract: The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

Abstract: Some aspects of the technology described herein relate to configuring an ultrasound device to perform a three-dimensional ultrasound imaging sweep, and displaying ultrasound images and segmented portions of the ultrasound images as the ultrasound images are collected during the three-dimensional ultrasound imaging sweep. Certain aspects relate to displaying an ultrasound image collected by an ultrasound device and configuring the ultrasound device to perform a three-dimensional ultrasound imaging sweep based on the ultrasound image collected by the ultrasound device.

Abstract: A crowd type classification system of an aspect of the present invention includes: a staying crowd detection unit that detects a local region indicating a crowd in staying from a plurality of local regions determined in an image acquired by an image acquisition device; a crowd direction estimation unit that estimates a direction of the crowd for an image of a part corresponding to the detected local region, and appends the direction of the crowd to the local region; and a crowd type classification unit that classifies a type of the crowd including a plurality of staying persons for the local region to which the direction is appended by using a relative vector indicating a relative positional relationship between two local regions and directions of crowds in the two local regions, and outputs the type and positions of the crowds.

Abstract: The present disclosure is directed towards computer-based systems and methods for evaluating a user's body motion based on motion data obtained via a series of wireless sensors attached to a user's body. In one embodiment, a computer-implemented method is disclosed herein. A server system receives motion data from one or more input devices. The motion data corresponds to movement of a user. The server system generates a motion profile based on at least the motion data received from the one or more input devices. The server system retrieves a pre-defined target motion profile from a database structure. The server system objectively evaluating the extracted motion profile by comparing one or more parameters of the generated motion profile with one or more parameters of the retrieved pre-defined target motion profile.

Abstract: Head-mounted augmented reality (AR) devices can track pose of a wearer's head to provide a three-dimensional virtual representation of objects in the wearer's environment. An electromagnetic (EM) tracking system can track head or body pose. A handheld user input device can include an EM emitter that generates an EM field, and the head-mounted AR device can include an EM sensor that senses the EM field. EM information from the sensor can be analyzed to determine location and/or orientation of the sensor and thereby the wearer's pose. An improved or optimized pose can be provided by reverse-estimating a reverse EM measurement matrix and optimizing the pose based on a comparison between the reverse EM measurement matrix and an EM measurement matrix measured by the EM sensor.

Abstract: A method may include obtaining an infrared image of an object and determining a difference of Gaussian image that represents features of the infrared image that have spatial frequencies within a spatial frequency range defined by a first Gaussian operator and a second Gaussian operator. The method may also include identifying one or more blob regions within the difference of Gaussian image. Each blob region of the one or more blob regions includes a region of connected pixels in the difference of Gaussian image. The method may further include, based on identifying the one or more blob regions within the difference of Gaussian image, determining that the infrared image represents the object illuminated by a pattern projected onto the object by an infrared projector.

Abstract: The present invention relates to a method for determining one or more intrinsic properties of a DNA component from a plurality of measurements obtained over a time period from a cell culture, with each cell comprising the DNA component, wherein the DNA component is involved in transcription of one or more target signals, wherein the plurality of measurements comprises measurements relating to the density of the cell culture over the time period and measurements relating to the amount of the one or more target signals in the cell culture over the time period.

Abstract: The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

Abstract: Methods and systems disclosed herein may quantify a representation of a type of input an image analysis system should expect. The image analysis system may be trained on the type of input the image analysis system should expect using a first image stream. A first model of the type of input that the image analysis system should expect may be built from the first image stream. After the first model is built, a second image, or a second image stream, may be compared to the first model to determine a difference between the second image, or second image stream, and the first image stream. When the difference is greater than or equal to a threshold, a drift may be detected and steps may be taken to determine the cause of the drift.

Abstract: a) A Gabor domain optical coherence microscopy (GD-OCM) system providing high resolution of structural and motion imaging of objects such as tissues is combined with the use of reverberant shear wave fields (RevSW) or longitudinal shear waves (LSW) and two novel mechanical excitation sources: a coaxial coverslip excitation (CCE) and a multiple pronged excitation (MPE) sources providing structured and controlled mechanical excitation in tissues and leading to accurate derivation of elastographic properties. Alternatively, general optical computed tomography (OCT) is combined with RevSW or LWC in the object to derive elastographic properties. The embodiments include (a) GD-OCM with RevSW; (b) GD-OCM with LSW; (c) General OCT with RevSW; and General OCT with LSW.

Abstract: The inventory capture system, method and apparatus (i.e., the inventory capture system) may provide for creating and updating an inventory of clothing for a user. The inventory capture system may use voice and image recognition to capture an inventory of clothing and provide users the ability to enhance the captured details about an inventory of clothing with annotations. Moreover, the inventory capture system may provide a way to facilitate retailers and users to leverage the user's existing inventory of clothing and augment the user's inventory of clothing with shared, purchased and/or rented clothing.