Abstract: A method for training a probabilistic encoder-decoder having a latent space, the method including: extracting different types of medical data for a group of individuals; creating a data matrix X including the extracted medical data, wherein each row of the data matrix X includes data for one of the group of individuals; creating condition matrix C including features to define a clinical condition, wherein each row of the condition matrix C includes the condition data for one of the group of individuals; and training the encoder and the decoder to learn the latent space by minimizing the reconstruction loss and using a regularization effect to force clinically similar inputs to be close together in the latent space.

Abstract: A method (100) for generating a textual description of a medical image, comprising: receiving (130) a medical image of an anatomical region, the image comprising one or more abnormalities; segmenting (140) the anatomical region in the received medical image from a remainder of the image; identifying (150) at least one of the one or more abnormalities in the segmented anatomical region; extracting (160) one or more features from the identified abnormality; generating (170), using the extracted features and a trained text generation model, a textual description of the identified abnormality; and reporting (180), via a user interface of the system, the generated textual description of the identified abnormality.

Abstract: A method (100) for generating a textual description of a medical image, comprising: receiving (130) a medical image of an anatomical region, the image comprising one or more abnormalities; segmenting (140) the anatomical region in the received medical image from a remainder of the image; identifying (150) at least one of the one or more abnormalities in the segmented anatomical region; extracting (160) one or more features from the identified abnormality; generating (170), using the extracted features and a trained text generation model, a textual description of the identified abnormality; and reporting (180), via a user interface of the system, the generated textual description of the identified abnormality.

Abstract: A non-transitory computer-readable medium stores instructions readable and executable by at least one electronic processor (20) to perform an atrial fibrillation (AF) detection method (100). The method includes: generating a time-frequency representation of an electrocardiogram (ECG) signal acquired over a time interval; processing the time-frequency representation using a neural network (NN) (32) to output probabilities for rhythms of a set of rhythms including at least atrial fibrillation; assigning a rhythm for the ECG signal based on the probabilities for the rhythms of the set of rhythms output by the neural network; and controlling a display device (24) to display the rhythm assigned to the ECG signal.

Abstract: A method of explaining a machine learning model, including: receiving a plurality of disease states for a patient over time from a database, wherein the disease states have a plurality of features; generating a plurality of locally faithful explanation models for the patient for the disease states based upon the machine learning model; calculating an explanation with respect to one feature of the plurality of features over time using the locally faithful explanation models; and calculating the importance of the one feature of the plurality of features over time based upon the plurality of locally faithful explanation models .

Abstract: A method of explaining a machine learning model, including: receiving a plurality of disease states for a patient over time from a database, wherein the disease states have a plurality of features; generating a plurality of locally faithful explanation models for the patient for each disease state based upon the machine learning model; calculating an explanation with respect to one feature of the plurality of features over time using the locally faithful explanation models; and calculating the importance of the one feature of the plurality of features over time based upon the plurality of locally faithful explanation models.

Abstract: A non-transitory computer-readable medium stores instructions readable and executable by at least one electronic processor (20) to perform an atrial fibrillation (AF) detection method (100). The method includes: generating a time-frequency representation of an electrocardiogram (ECG) signal acquired over a time interval; processing the time-frequency representation using a neural network (NN) (32) to output probabilities for rhythms of a set of rhythms including at least atrial fibrillation; assigning a rhythm for the ECG signal based on the probabilities for the rhythms of the set of rhythms output by the neural network; and controlling a display device (24) to display the rhythm assigned to the ECG signal.

Abstract: A system and method for visualizing and annotating temporal trends of an abnormal condition in patient data. A classification and visualization module detects one or more conditions in one or more images, e.g. X-ray images, and visualizes the condition on the image. A temporal disease state extraction module analyzes text, e.g. radiology reports, for indications of a change in the condition. A multimodal disease state comparison module fuses the extracted data into a compact representation of the condition changes over time.

Abstract: The present invention is related to the field of microfluidics and compound distribution within microfluidic devices and their associated systems. In one embodiment, present invention aims to solve the problem of molecule and compound absorbency into the materials making up laboratory equipment, microfluidic devices and their related infrastructure, without unduly restricting gas transport within microfluidic devices.

Abstract: The present invention is related to the field of microfluidics and compound distribution within microfluidic devices and their associated systems. In one embodiment, present invention aims to solve the problem of molecule and compound absorbency into the materials making up laboratory equipment, microfluidic devices and their related infrastructure, without unduly restricting gas transport within microfluidic devices.

Abstract: A system and method for performing image processing. The method includes receiving an image of a first modality and a real image of a second modality, the image of the first modality and the image of the second modality capturing respective images of a same subject, applying a first trained model to the image of the first modality to generate an artificial image mimicking the image of the second modality, applying a second trained model to the artificial image mimicking the image of the second modality and data of the image of the first modality, and outputting at least one conclusion regarding the generated artificial image.

Abstract: The present invention is related to high-content microscopy imaging of microfluidic cell culture systems. A method of high-content microfluidic device microscopy is contemplated, along with related statistical analysis and microfluidic device adaptors.

Abstract: The present invention is related to high-content microscopy imaging of microfluidic cell culture systems. A method of high-content microfluidic device microscopy is contemplated. along with related statistical analysis and microfluidic device adaptors.

Abstract: A filter for a water cooler includes a housing having a surface and a cavity with cavity ports. The filter end is adapted to be received in the housing. The filter end includes a cylindrical base having a surface and a neck extending from the surface. The neck has filter ports and a side surface. The side surface has oppositely directed axially extending elongated protrusions configured to be received in channels in the housing. The base surface includes a complex set of protrusions which are adapted to be received in a similarly configured set of recesses in the housing surface. The protrusions/recesses may take the form of letters, numbers or symbols. The filter end is be fully seated in the housing in bayonet-type fashion to connect the filter ports and the housing ports o permit water to flow through the filter from the water supply to the water cooler.

Abstract: A method (100) for generating a textual description of a medical image, comprising: receiving (130) a medical image of an anatomical region, the image comprising one or more abnormalities; segmenting (140) the anatomical region in the received medical image from a remainder of the image; identifying (150) at least one of the one or more abnormalities in the segmented anatomical region; extracting (160) one or more features from the identified abnormality; generating (170), using the extracted features and a trained text generation model, a textual description of the identified abnormality; and reporting (180), via a user interface of the system, the generated textual description of the identified abnormality.

Abstract: A filter for a water cooler includes a housing having a surface and a cavity with cavity ports. The filter end is adapted to be received in the housing. The filter end includes a cylindrical base having a surface and a neck extending from the surface. The neck has filter ports and a side surface. The side surface has oppositely directed axially extending elongated protrusions configured to be received in channels in the housing. The base surface includes a complex set of protrusions which are adapted to be received in a similarly configured set of recesses in the housing surface. The protrusions/recesses may take the form of letters, numbers or symbols. The filter end is be fully seated in the housing in bayonet-type fashion to connect the filter ports and the housing ports o permit water to flow through the filter from the water supply to the water cooler.

Abstract: A method of explaining a machine learning model, including: receiving a plurality of disease states for a patient over time from a database, wherein the disease states have a plurality of features; generating a plurality of locally faithful explanation models for the patient for each disease state based upon the machine learning model; calculating an explanation with respect to one feature of the plurality of features over time using the locally faithful explanation models; and calculating the importance of the one feature of the plurality of features over time based upon the plurality of locally faithful explanation models .

Abstract: A water inlet pipe connects a water supply to a faucet. A water flow control valve in the water inlet pipe regulates the flow of water through the water inlet pipe from the water supply to the faucet. A drip tray located beneath the faucet captures water overflow. A conduit connects the drip tray a storage container such that water in the drip tray drains into the storage container. A water level sensor associated with the storage container generates a overflow signal when the water level in the storage container reaches a pre-set level. The water flow control valve automatically prevents water flow through the water inlet pipe to the faucet in response to the overflow signal. A visible display and a sound generator are also energized in response to the alarm signal.