Abstract: Systems and methods are provided for provided for automatic evaluation of sperm morphology. An image of a semen sample is obtained, and at least a portion of the image is provided to a convolutional neural network classifier. The convolutional neural network classifier evaluates the portion of the image to assign to the portion of the image a set of likelihoods that the portion of the image belongs to a plurality of output classes representing the morphology of sperm within the portion of the image. A metric is assigned to the semen sample based on the likelihoods assigned by the convolutional neural network.

Abstract: Systems and methods are provided for provided for automatic evaluation of a human embryo. An image of the embryo is obtained and provided to a neural network to generate a plurality of values representing the morphology of the embryo. The plurality of values representing the morphology of the embryo are evaluated at an expert system to provide an output class representing one of a current quality of the embryo, a future quality of the embryo, a likelihood that implantation of the embryo will be successful, and a likelihood that implantation of the embryo will result in a live birth.

Abstract: A system for virus detection in a sample from a subject includes a microchip comprising at least one channel containing the sample from the subject and a mobile device. The sample is processed with nanoparticles and a catalyzer that are configured to generate gas bubbles in the presence of a target virus on a surface of the microchip. The mobile device includes a camera configured to acquire an image of the microchip containing the sample from the subject, a neural network configured to receive the acquired image and to generate a probability regarding the presence of the target virus in the sample from the subject based on the acquired image, and a display coupled to the neural network and configured to display the probability regarding presence of the target virus in the sample from the subject.

Abstract: Systems and methods are provided for provided for automatic evaluation of a human embryo. An image of the embryo is obtained and provided to a neural network to generate a plurality of values representing the morphology of the embryo. The plurality of values representing the morphology of the embryo are evaluated at an expert system to provide an output class representing one of a current quality of the embryo, a future quality of the embryo, a likelihood that implantation of the embryo will be successful, and a likelihood that implantation of the embryo will result in a live birth.

Abstract: Systems and methods are provided for determining a clinical parameter representing the location of interest within a reproductive cellular structure. An image of the reproductive cellular structure is obtained and provided to a neural network to generate the clinical parameter. The clinical parameter is stored on a non-transitory computer readable medium.

Abstract: Systems and methods are provided for fully automated screening for aneuploidy in a human embryo. An image of the embryo is obtained at an associated imager and provided to a neural network to generate a first clinical parameter. A set of at least one parameter representing one of biometric parameters of one of a patient receiving the embryo, an egg utilized to produce the human embryo, a sperm used to create the embryo, a sperm donor who provided sperm used to create the embryo, and an egg donor who provided the egg is retrieved, and a second clinical parameter is generated from the set of at least one parameter at a predictive model. A composite parameter, representing a likelihood of aneuploidy in the embryo, is generated from the first clinical parameter and the second clinical parameter.

Abstract: Systems and methods are provided for medical image classification of images from varying sources. A set of microscopic medical images are acquired, and a first neural network module configured to reduce each of the set of microscopic medical images to a feature representation is generated. The first neural network module, a second neural network module, and a third neural network module are trained on at least a subset of the set of microscopic medical images. The second neural network module is trained to receive feature representation associated with an image of the microscopic images and classify the image into one of a first plurality of output classes. The third neural network module is trained to receive the feature representation, classify the image into one of a second plurality of output classes based on the feature representation, and provide feedback to the first neural network module.

Abstract: Devices and methods for performing dielectrophoresis are described. The devices contain sample channel which is separated by physical barriers from electrode channels which receive electrodes. The devices and methods may be used for the separation and analysis of particles in solution, including the separation and isolation of cells of a specific type. As the electrodes do not make contact with the sample, electrode fouling is avoided and sample integrity is better maintained.

Abstract: Systems and methods are provided for assigning a quality parameter to a reproductive cellular structure. An image of the reproductive cellular structure is obtained. The image of the reproductive cellular structure is provided to a neural network to generate a value representing a morphology of the reproductive cellular structure. The value is compared to a predefined standard to provide a quality assurance metric representing one of a medical personnel, a facility, a growth medium, and an identity of the reproductive cellular structure.

Abstract: Systems and methods are provided for provided for automatic evaluation of a human embryo. An image of the embryo is obtained and provided to a neural network to generate a plurality of values representing the morphology of the embryo. The plurality of values representing the morphology of the embryo are evaluated at an expert system to provide an output class representing one of a current quality of the embryo, a future quality of the embryo, a likelihood that implantation of the embryo will be successful, and a likelihood that implantation of the embryo will result in a live birth.

Abstract: Systems and methods are provided for provided for automatic evaluation of a human embryo. An image of the embryo is obtained and provided to a neural network to generate a plurality of values representing the morphology of the embryo. The plurality of values representing the morphology of the embryo are evaluated at an expert system to provide an output class representing one of a current quality of the embryo, a future quality of the embryo, a likelihood that implantation of the embryo will be successful, and a likelihood that implantation of the embryo will result in a live birth.

Abstract: Systems and methods are provided for determining if a subject has a biological condition from a dried fluid sample. A fluid sample from a subject is dried in a microfluidic device to provide a dried fluid sample. The dried fluid sample is imaged at a camera to provide a sample image, and the sample image is provided to a computer vision mode. At the computer vision model, it is determined if the sample image contains a ferning pattern indicative of a biological condition of the subject.

Abstract: Systems and methods are provided for provided for automatic evaluation of sperm morphology. An image of a semen sample is obtained, and at least a portion of the image is provided to a convolutional neural network classifier. The convolutional neural network classifier evaluates the portion of the image to assign to the portion of the image a set of likelihoods that the portion of the image belongs to a plurality of output classes representing the morphology of sperm within the portion of the image. A metric is assigned to the semen sample based on the likelihoods assigned by the convolutional neural network.

Abstract: Systems and methods are provided for evaluating the quality of a semen sample at a mobile device. An assembly includes an optical assembly with at least one lens and a housing configured to engage with the mobile device such that an axis of the optical assembly is substantially aligned with a camera of the mobile device. The optical assembly is contained within the housing. A microfluidic chip includes a reservoir to hold the semen sample. The microfluidic chip engages with the housing such that the reservoir is aligned with the axis of the optical assembly.

Abstract: Systems and methods are provided for provided for automatic evaluation of a human embryo. An image of the embryo is obtained and provided to a neural network to generate a plurality of values representing the morphology of the embryo. The plurality of values representing the morphology of the embryo are evaluated at an expert system to provide an output class representing one of a current quality of the embryo, a future quality of the embryo, a likelihood that implantation of the embryo will be successful, and a likelihood that implantation of the embryo will result in a live birth.

Abstract: Systems and methods are provided for evaluating the quality of a semen sample at a mobile device. An assembly includes an optical assembly with at least one lens and a housing configured to engage with the mobile device such that an axis of the optical assembly is substantially aligned with a camera of the mobile device. The optical assembly is contained within the housing. A microfluidic chip includes a reservoir to hold the semen sample. The microfluidic chip engages with the housing such that the reservoir is aligned with the axis of the optical assembly.

Abstract: Systems and methods are provided for evaluating the quality of a semen sample at a mobile device. An assembly includes an optical assembly with at least one lens and a housing configured to engage with the mobile device such that an axis of the optical assembly is substantially aligned with a camera of the mobile device. The optical assembly is contained within the housing. A microfluidic chip includes a reservoir to hold the semen sample. The microfluidic chip engages with the housing such that the reservoir is aligned with the axis of the optical assembly.

Abstract: Devices and methods for performing dielectrophoresis are described. The devices contain sample channel which is separated by physical barriers from electrode channels which receive electrodes. The devices and methods may be used for the separation and analysis of particles in solution, including the separation and isolation of cells of a specific type. As the electrodes do not make contact with the sample, electrode fouling is avoided and sample integrity is better maintained.

Abstract: Devices and methods for performing dielectrophoresis are described. The devices contain sample channel which is separated by physical barriers from electrode channels which receive electrodes. The devices and methods may be used for the separation and analysis of particles in solution, including the separation and isolation of cells of a specific type. As the electrodes do not make contact with the sample, electrode fouling is avoided and sample integrity is better maintained.

Abstract: Systems and methods are provided for evaluating the quality of a semen sample at a mobile device. An assembly includes an optical assembly with at least one lens and a housing configured to engage with the mobile device such that an axis of the optical assembly is substantially aligned with a camera of the mobile device. The optical assembly is contained within the housing. A microfluidic chip includes a reservoir to hold the semen sample. The microfluidic chip engages with the housing such that the reservoir is aligned with the axis of the optical assembly.