Abstract: A method and user device for determining a unified Parkinson's disease rating scale (UPDRS) value associated with a user of the user device include obtaining video data associated with a movement of a body part of the user. The UPDRS value is determined using a model and the video data associated with the movement of the body part of the user. The UPDRS value is provided to permit an evaluation of the user based on the UPDRS value.

Abstract: A method, computer program, and computer system are provided for image segmentation. Image data, such as biological image data, is received. One or more objects associated with the received image data is detected. One or more regions of interest are determined within the receive image data corresponding to one or more segments based on the detected objects.

Abstract: A method and device for generating a three dimensional (3D) bounding box of a region of interest (ROI) of a patient include receiving a two dimensional (2D) maximum intensity projection (MIP) image that is an axial view of the patient and a 2D MIP image that is a sagittal view of the patient. A first 2D bounding box of the ROI of the patient and a second 2D bounding box of the ROI of the patient are detected using the 2D MIP images. A 3D MIP image of the patient is received, and the 3D bounding box of the ROI of the patient is generated using the 3D MIP image, the first 2D bounding box, and the second 2D bounding box. The 3D MIP image including the 3D bounding box is provided.

Abstract: Systems and methods for obtaining hand images are provided. A method, performed by at least one processor that implements at least one network, includes obtaining a single source image, a three-dimensional (3D) hand pose of a first hand in the single source image, and a 3D target hand pose; and generating an image of a second hand, that has an appearance of the first hand and a pose of the 3D target hand pose, based on the single source image, the 3D hand pose, and the 3D target hand pose.

Abstract: A method and user device for providing a unified Parkinson's disease rating scale (UPDRS) value by a user device includes generating, by a sensor of the user device, sensor data based on a user of the user device manipulating the user device. The UPDRS value is determined based on the sensor data and a deep neural network (DNN) model. The UPDRS value is provided to permit an evaluation of the user based on the UPDRS value.

Abstract: A method, computer program, and computer system are provided for image segmentation. Image data, such as biological image data, is received. One or more objects associated with the received image data is detected. One or more regions of interest are determined within the receive image data corresponding to one or more segments based on the detected objects.

Abstract: A method, computer program, and computer system is provided for text error identification and correction. A text input having a phonetic component and a glyphic component is received. Information corresponding to the phonetic component and the glyphic component is coded as a fixed-length sequence. One or more candidate replacement words corresponding to the fixed-length sequence are identified. At least a portion of the text input is replaced with a candidate replacement word from among the one or more candidate replacement words.

Abstract: There is included an apparatus and system including image segmentation code, configured to cause at least one hardware processor to segment an image of a person's hand from an input image, and classification code configured to cause the at least one processor to classify the segmented image of the person's hand according to at least one predefined pose.

Abstract: There is included an apparatus and system including video capture code configured to control a camera of a mobile phone to capture a video of at least a portion of skin, extraction code configured to extract at least one photoplethysmogram (PPG) signal from the video, determination code configured to determine a peripheral oxygen saturation (SpO2) value based on the PPG signal with respect to a blood flow at the portion of skin, and display code configured to control a display of the mobile phone to display the SpO2 value.

Abstract: A method and user device for determining a unified Parkinson's disease rating scale (UPDRS) value associated with a user of the user device include obtaining video data associated with a movement of a body part of the user. The UPDRS value is determined using a model and the video data associated with the movement of the body part of the user. The UPDRS value is provided to permit an evaluation of the user based on the UPDRS value.

Abstract: A method and apparatus include receiving a three dimensional (3D) non-contrast computed tomography (NCCT) image of a head including a hematoma. A plurality of two dimensional (2D) images of the head including the hematoma are generated using the 3D NCCT image of the head including the hematoma. A plurality of 2D hematoma images are generated using a first 2D convolutional neural network (CNN) based on the plurality of 2D images. A 3D region of interest (ROI) that encompasses the hematoma is identified based on the plurality of 2D hematoma images. A plurality of 2D images that correspond to the ROI are generated. A hematoma expansion (HE) prediction score is determined using a second CNN based on the plurality of 2D images that correspond to the ROI. The HE prediction score is provided.

Abstract: A method, computer program, and computer system is provided for text error identification and correction. A text input having a phonetic component and a glyphic component is received. Information corresponding to the phonetic component and the glyphic component is coded as a fixed-length sequence. One or more candidate replacement words corresponding to the fixed-length sequence are identified. At least a portion of the text input is replaced with a candidate replacement word from among the one or more candidate replacement words.

Abstract: A method, computer program, and computer system are provided for image segmentation. Image data, such as biological image data, is received. One or more objects associated with the received image data is detected. One or more regions of interest are determined within the receive image data corresponding to one or more segments based on the detected objects.

Abstract: A method and user device for determining a unified Parkinson's disease rating scale (UPDRS) value associated with a user of the user device include obtaining video data associated with a movement of a body part of the user. The UPDRS value is determined using a model and the video data associated with the movement of the body part of the user. The UPDRS value is provided to permit an evaluation of the user based on the UPDRS value.

Abstract: Systems and methods for obtaining hand images are provided. A method, performed by at least one processor that implements at least one network, includes obtaining a single source image, a three-dimensional (3D) hand pose of a first hand in the single source image, and a 3D target hand pose; and generating an image of a second hand, that has an appearance of the first hand and a pose of the 3D target hand pose, based on the single source image, the 3D hand pose, and the 3D target hand pose.

Abstract: An approach for determining a heart rate of a subject is performed by at least one processor and includes obtaining video data of the subject; detecting a face of the subject in the video data; selecting at least one region of interest (ROI) included in the face; acquiring photoplethysmography (PPG) signals based on the at least one ROI; and determining the heart rate of the subject based on the PPG signals

Abstract: A method, computer program, and computer system is provided for query matching of sentences based on co-attention scores. Two or more query inputs to a neural network are received. A correlation factor between the two or more query input is identified based on attention weights. A feature vector is generated based on the attention weights. A probability value corresponding to the two or more query inputs is determined based on the generated feature vector.

Abstract: Systems and methods for marker-free motion capture are provided. A method includes: obtaining a plurality of videos of a body of a person; estimating a three dimensional (3D) pose of the person based on the plurality of videos without depending on any marker on the person, the estimating including obtaining a set of 3D body joints; obtaining an animation of motion of the set of 3D body joints that corresponds to motion of the person during a time period; performing an analysis of the motion of the set of 3D body joints; and indicating a rehabilitation evaluation result of the analysis or a rehabilitation training suggestion, based on the analysis, via a display or a speaker.

Abstract: There is included an apparatus and system including an intra-heartbeat (HB) extraction code configured to extract intra-HB features from electrocardiography (ECG) signals, and an inter-HB extraction code configured to extract inter-HB features from the ECG signals, and at least one attention mechanism code configured to control at least one of the intra-HB extraction code and inter-HB extraction code based on at least one attention mechanism.

Abstract: A method and apparatus include receiving a first sentence including a first set of words, and a second sentence including a second set of words. A first set of vectors corresponding to the first set of words of the first sentence, and a second set of vectors corresponding to the second set of words of the second sentence are generated using a word embedding model. A similarity matrix based on the first set of vectors and the second set of vectors is generated. An alignment score associated with the first set of vectors and the second set of vectors is determined using the similarity matrix. The alignment score is transmitted to permit information retrieval based on a similarity between the first sentence and the second sentence.