Alibaba Group Holding Limited

Siemens Healthcare Gmbh

Alibaba (china) Co., Ltd.

Ying Chi

Xiansheng Hua

Yu Ying Wang

Xuansong Xie

Chao Liu

Lei Zhang

Shaohua Kevin Zhou

Yu Wang

Tommaso Mansi

Shanhui Sun

Yefeng Zheng

Ning Liu

David D Liu

Li Zhang

Zhoubing Xu

Daguang Xu

Chen Chen

Julian Krebs

Wei Jia Liu

Wei Liu

Nora Hünemohr

Pavlo Dyban

Peiran Jiang

Prediction of an affinity between a drug and a target is disclosed. The drug and the target for interacting with the drug are acquired. An interaction is caused between the drug and the target to determine the compound. Topological structure graphs for labeling spatial characteristics of atoms in the compound are computed. An affinity between the drug and the target based on the topological structure graphs is determined.

Method and system for predicting affinity between drug and target

Embodiments of the disclosure provide a method, apparatus, and device for data processing. The method comprises: obtaining data of at least two different modalities, the data comprising at least first data and second data, the first data and second stored in respective data sources; determining an overlapping keyword correlating the first data and the second data by analyzing textual descriptions associated with the first data and second data and identifying the overlapping keyword as appearing in a textual description of the first data and in a textual description of the second data; and storing the first data and the second data in an associative manner based on the overlapping keyword, the associative manner generated using the overlapping keyword.

Data processing method, apparatus, and device

The present application discloses a method, device, and system for processing a medical image. The method includes obtaining a source spinal image, identifying one or more vertebral bodies and one or more intervertebral discs comprised in the source spinal image, determining the vertebral body recognition results corresponding to the one or more vertebral bodies and the intervertebral disc recognition results corresponding to the one or more intervertebral discs, and determining target recognition results corresponding to the source spinal image based at least in part one on one or more of the vertebral body recognition results and the intervertebral disc recognition results.

Processing method, model training method, means, and storage medium for spinal images

Embodiments of the disclosure provide methods, apparatuses, and computer-readable media for generating image reports. In one embodiment, the method includes: obtaining an image to be analyzed; determining at least one reference image corresponding to the image to be analyzed, the at least one reference image corresponding to a respective reference image report; and generating, based on the reference image report, an image report corresponding to the image to be analyzed. In the method for generating an image report provided by the embodiments, by obtaining an image to be analyzed is obtained, at least one reference image corresponding to the image to be analyzed is determined; and an image report corresponding to the image to be analyzed is generated based on a respective reference image report corresponding to the at least one reference image. Therefore, medical staff are assisted in quickly writing an image report, thereby ensuring the quality and the efficiency of the image report, reducing labor costs and time costs required for collating the image report, and further improving the practicability of the method.

Method and apparatus for generating image reports

Various techniques are provided for generating reports of three dimensional (3D) images. The techniques include identifying a plurality of volume features in a 3D image using a first machine learning (ML) module trained with annotated 3D images, and identifying a plurality of semantic representations associated with the 3D image using a second ML module trained with the annotated 3D images and reports associated with the annotated 3D images. The techniques further include generating a report of the 3D image based on the volume features and the semantic representations using a third ML module trained with the reports and outputs generated by the first ML module and the second ML module using the annotated 3D images and the reports.

Generating reports of three dimensional images

Embodiments can provide a method for atlas-based contouring, comprising constructing a relevant atlas database; selecting one or more optimal atlases from the relevant atlas database; propagating one or more atlases; fusing the one or more atlases; and assessing the quality of one or more propagated contours.

Atlas-based contouring of organs at risk for radiation therapy

Growing community of inventors

Beijing, China

Ying Chi