Tencent America LLC

International Business Machines Corporation

Columbia University

Sap Ag

Citibank, N.a.

Wei Fan

Hui Tang

Lianyi Han

Yusheng Xie

Min Tu

Tao Yang

Shih-Yao Lin

Kun Wang

Haixun Wang

Chao Huang

Shangqing Zhang

Philip Shilung Yu

Yaliang Li

Zhimin Huo

Nan Du

Zhen Qian

Xiaozhong Chen

Xu Wang

Qian Zhen

Philip Shi-lung Yu

Deepak Srinivas Turaga

Salvatore J Stolfo

Srinivasan Parthasarathy

Zeyu You

Chang-Shing Perng

Jing Gao

Wenke Lee

Shihyao Lin

Guy Maring Lohman

Nimrod Megiddo

Joel Leonard Wolf

Olivier Verscheure

Nagui Halim

David Everett Simmen

Henrique Andrade

James R Giles

Lisa Amini

Kirsten Weale Hildrum

Volker Gerhard Markl

Deepak Rajan

Jun Rao

Rohit Wagle

Mark C Johnson

Philip Shi-Lung Yu

Daniel Schutzer

Xifeng Yan

Julia Stoyanovich

Hong Cheng

Matthew Miller

Yufan Xue

Huanrui Hu

William Hull Forster, Jr

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.

System and method for instance segmentation in pathological images using object-guided framework

There is included a method and apparatus comprising computer code configured to cause a processor or processors to perform obtaining video data including at least one body part of a person, selecting keypoints of the at least one body part based on a predetermined rehabilitation category, extracting a motion feature of the at least one body part from the video data, scoring the motion feature based on the predetermined rehabilitation category, and generating a display illustrating the motion feature and said scoring of the motion feature.

Vision-based motion capture system for rehabilitation training

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.

Efficient and compact text matching system for sentence pairs

A method and apparatus for performing a biosignal analysis task using a set of models includes receiving an input biosignal. Information that identifies the biosignal analysis task to be performed in association with the input biosignal is received. A waveform model and a digital signal processing (DSP) model are selected. A first type of feature and a second type of feature of the input biosignal are identified. An analysis model is selected, and the biosignal analysis task is performed using the analysis model.

Digital signal processing assistant modeling method for biosignal analysis

A method and apparatus include receiving, by a device, medical information associated with a user. Inquiry information is determined based on the medical information associated with the user and a reinforcement learning model. The inquiry information is provided to permit response information to be received. The response information is received based on providing the inquiry information. Diagnosis information is determined based on the medical information and the response information using a machine learning model. The diagnosis information is provided to a set of devices via a network.

System and method for clinical decision support system with inquiry based on reinforcement learning

A method and apparatus are provided that includes, in a same framework, storing an artificial intelligence (AI) model, loading the AI model into a serving platform, loading and testing a test unit against the AI model loaded into the serving platform, and collecting reports from results of storing the AI model, loading the AI model into the serving platform and testing the test unit.

Machine learning model full life cycle management framework

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.

User device based Parkinson's disease detection

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.

Synthesizing 3D hand pose based on multi-modal guided generative networks

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.

System and method for identifying target regions prior to organs at risk segmentation

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.

User device based parkinson disease detection

A method, computer program, and computer system for detecting and classifying atrial fibrillation by receiving data corresponding to an electrocardiogram (ECG) associated with a patient, extracting RR intervals from the received ECG data, determining previous RR intervals for each of the extracted RR intervals and aggregating features associated with the RR intervals and the previous RR intervals. Patterns associated with the aggregated features are classified, and the computer may determine that a sample of the ECG data corresponding to one or more of the classified patterns contains a pattern associated with atrial fibrillation.

Deep neural network on ECG Poincare plot for atrial fibrillation classification

Embodiments of the present disclosure include a method, device and computer readable medium involving receiving image data of one or more coronary arteries, generating a binary segmentation indicating presence of calcium in the one or more coronary arteries from the image data, generating a branch density of the one or more coronary arteries, and assigning a coronary artery label from the branch density to the binary segmentation such that at least one indication of presence of calcium of the binary segmentation is labeled as present in a specific one of the one or more coronary arteries.

System and method for coronary calcium deposits detection and labeling

A method and device for performing electrocardiography (ECG) analysis, the method including receiving ECG data that is from one or more leads, generating an image based on the ECG data, obtaining a feature map based on the image, inputting the feature map to a first neural network, the first neural network configured to generate an output based on the feature map inputted, inputting the output of the first neural network to a second neural network, the second neural network configured to obtain at least one temporal feature of the image based on the output of the first neural network and a previous state of the second neural network, and classifying a signal included in the ECG data based on the at least one temporal feature obtained by the second neural network.

Framework for performing electrocardiography analysis

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.

Framework for chinese text error identification and correction

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Wei Fan