Ling Zhang

US Patent:

8556882, Oct 15, 2013

Filed:

Apr 22, 2010

Appl. No.:

13/266280

Inventors:

Richard A. Morgan - Columbia MD, US
Steven A. Rosenberg - Potomac MD, US
Ling Zhang - Rockville MD, US
Nicholas P. Restifo - Chevy Chase MD, US

Assignee:

The United States of America, as represented by the Secretary, Department of Health and Human Services - Washington DC

International Classification:

C12N 1/15
C12N 1/13
C12N 1/21

US Classification:

604522, 536 235, 514 44 R

Abstract:

The invention provides an isolated or purified nucleic acid comprising a nucleotide sequence encoding a nuclear factor of activated T-cells (NFAT) promoter operatively associated with a nucleotide sequence encoding IL-12. The invention also provides a nucleic acid comprising a nucleotide sequence encoding a nuclear factor of activated T-cells (NFAT) promoter operatively associated with a nucleotide sequence encoding IL-12, wherein the NFAT promoter is located 3′ of the nucleotide sequence encoding IL-12. Also provided are related recombinant expression vectors, host cells, populations of cells, and pharmaceutical compositions. The invention further provides the use of the inventive nucleic acids or related materials in the treatment or prevention of cancer or an infectious disease in a mammal and in the induction of IL-12 expression in a mammal.

US Patent:

55784860, Nov 26, 1996

Filed:

Aug 5, 1994

Appl. No.:

8/286470

Inventors:

Ling Y. Zhang - Rockville MD

Assignee:

International TLB Research Institute, Inc. - Poolesville MD

International Classification:

C12N 100
C05F 1108

US Classification:

435243

Abstract:

A microbial fertilizer that constitutes a symbiotic association of several recombinant microbial species is described. The fertilizer contains four streptomyces strains and two yeast strains. The streptomyces strains include a nitrogen fixing strain, a phosphorus decomposer, a potassium decomposer and a coal waste decomposer. The yeast strains produce growth factors and energy required by the streptomyces.

US Patent:

20220292689, Sep 15, 2022

Filed:

Mar 9, 2021

Appl. No.:

17/195908

Inventors:

- Shenzhen, CN
Ling Zhang - Bethesda MD, US

International Classification:

G06T 7/174
G06T 7/11
G16H 30/40

Abstract:

A Pancreatic Ductal Adenocarcinoma (PDAC) image segmentation method, an electronic device, and a storage medium are provided. In the PDAC image segmentation method, a first model is trained using a first data set; and a second model is trained using a second data set. A third data set is obtained by annotating a to-be-annotated data set using the first model and the second model and a third model is trained using a fourth data set. A training set is obtained by modifying the first data set and the third data set using the third model and a segmentation model is obtained by training an nnUNet using the training set. A to-be-segmented PDAC image is input into the segmentation model, and a segmentation result is obtained. By utilizing the PDAC image segmentation method, a more accurate PDAC image segmentation is achieved.

US Patent:

20220245810, Aug 4, 2022

Filed:

Feb 2, 2021

Appl. No.:

17/165369

Inventors:

- Shenzhen, CN
Ling Zhang - Bethesda MD, US
Le Lu - Bethesda MD, US

International Classification:

G06T 7/00
G06K 9/62
G06K 9/46
G16H 30/40

Abstract:

A preoperative survival prediction method and a computing device applying the method include constructing a data seta according to a plurality of enhanced medical images and a resection margin of each enhanced medical image and obtaining a plurality of training data sets from the constructed data set. For each training data set, multi-task prediction models are trained. A target multi-task prediction model is selected from the plurality, and a resection margin prediction value and a survival risk prediction value are obtained by predicting an enhanced medical image to be measured through the target multi-task prediction model. The multi-task prediction model more effectively captures the changes over time of the tumor in multiple stages, so as to enable a joint prediction of a resection margin prediction value and a survival risk prediction value.

US Patent:

20220180506, Jun 9, 2022

Filed:

Mar 26, 2021

Appl. No.:

17/213343

Inventors:

- Shenzhen, CN
Kai CAO - Shanghai, CN
Ling ZHANG - Bethesda MD, US
Jiawen YAO - Bethesda MD, US
Le LU - Bethesda MD, US

International Classification:

G06T 7/00
G06T 7/11
G06T 17/20
G16H 20/00
A61B 5/00

Abstract:

A method for pancreatic mass diagnosis and patient management includes: receiving CT images of a pancreas of a patient, the pancreas of the patient including a mass; performing a segmentation process on the CT images of the pancreas and the mass to obtain a segmentation mask of the pancreas and the mass of the patient; performing a mask-to-mesh process on the segmentation mask of the pancreas and the mass of the patient to obtain a mesh model of the pancreas and the mass of the patient; performing a classification process on the mesh model of the pancreas and the mass of the patient to identify a type and a grade of a segmented pancreatic mass; and outputting updated CT images of the pancreas of the patient, the updated CT images including the segmented pancreatic mass highlighted thereon and the type and the grade of the segmented pancreatic mass annotated thereon.

US Patent:

20210073995, Mar 11, 2021

Filed:

Sep 11, 2019

Appl. No.:

16/568161

Inventors:

- Santa Clara CA, US
Holger Reinhard Roth - Rockville MD, US
Ziyue Xu - Reston VA, US
Fausto Milletari - Munchen, DE
Ling Zhang - Rockville MD, US
Te-Chung Isaac Yang - San Ramon CA, US
Daguang Xu - Potomac MD, US

International Classification:

G06T 7/10
G06T 7/00
G06T 5/00
G06N 3/04

Abstract:

In at least one embodiment, a reinforcement-learning-based searching approach is used to produce a training configuration for a machine-learning model. In at least one embodiment, 3D medical image segmentation is performed using learned image preprocessing parameters.

US Patent:

20200394459, Dec 17, 2020

Filed:

Jun 17, 2019

Appl. No.:

16/443549

Inventors:

- Santa Clara CA, US
Xiaosong Wang - Rockville MD, US
Hoo Chang Shin - Rockville MD, US
Dong Yang - North Bethesda MD, US
Holger Roth - Rockville MD, US
Daguang Xu - Potomac MD, US
Ling Zhang - Rockville MD, US
Fausto Milletari - Munchen, DE

International Classification:

G06K 9/62
G06T 7/11
G06N 3/08
G06N 5/04
G16B 45/00
G16B 25/00
G16B 40/00

Abstract:

Apparatuses, systems, and techniques to generate synthesized images including digital representations of groups of cells blended realistically with appropriate background images. In at least one embodiment, background image data and gene expression data are fused together to generate such a synthesized image using one or more neural networks.

US Patent:

20200293828, Sep 17, 2020

Filed:

Mar 9, 2020

Appl. No.:

16/813673

Inventors:

- Santa Clara CA, US
Ziyue Xu - Reston VA, US
Dong Yang - North Bethesda MD, US
Holger Reinhard Roth - Rockville MD, US
Andriy Myronenko - San Francisco CA, US
Daguang Xu - Potomac MD, US
Ling Zhang - Rockville MD, US

International Classification:

G06K 9/62
G06N 3/063
G06N 3/08
G06N 3/04
G06K 9/00

Abstract:

Apparatuses, systems, and techniques to perform training of neural networks using stacked transformed images. In at least one embodiment, a neural network is trained on stacked transformed images and trained neural network is provided to be used for processing images from an unseen domain distinct from a source domain, wherein stacked transformed images are transformed according to transformation aspects related to domain variations.